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Evidence for general right- mixed- and left-sidedness in self-reportedhandedness footedness eyedness and earedness and a primacyof footedness in a large-sample latent variable analysis

Ulrich S Tran n Stefan Stieger Martin Voracek

Department of Basic Psychological Research and Research Methods School of Psychology University of Vienna Liebiggasse 5 A-1010 Vienna Austria

a r t i c l e i n f o

Article historyReceived 27 November 2013

Received in revised form

22 July 2014

Accepted 25 July 2014Available online 2 August 2014

Keywords

Laterality

Sidedness

Latent variable analysisPsychometric analysis

Taxometric analysis

a b s t r a c t

Lateral preferences are important for the study of cerebral lateralization and may be indicative of neurobehavioral disorders neurodevelopmental instability and de1047297cits in lateralization Previous

studies showed that self-reported preferences are also concordantly interrelated suggesting a commongenetic or biological origin sidedness However with regard to the assessment and classi1047297cation of

lateral preferences there is a dearth of psychometric studies but a need for psychometrically validatedinstruments that can be reliably used in applied research Based on three independent large samples

(total N 415100) this study investigated the psychometric properties of widely-used lateral preferencescales of handedness footedness eyedness and earedness Preferences were consistently and replicablycategorical consisting of right mixed and left preferences each underlining that primarily qualitative

rather than quantitative differences differentiate lateral preferences Right- mixed- and left-sidednessunderlay the individual preferences but sidedness alone could not fully explain the observed inter-

relations Footedness was the single most important indicator of sidedness Our data were furtherconsistent with predictions of right shift theory and corroborated a lsquopull-to-concordancersquo in handndashfoot

preferences We recommend the use of psychometrically validated scales and of a trichotomousclassi1047297cation of lateral preferences in future research but conclude that handedness may be a biased

indicator of underlying sidedness Footedness needs to be examined more closely with regard to cerebrallateralization neurodevelopmental disorders and neurodevelopmental instability

amp 2014 Published by Elsevier Ltd

1 Introduction

The preference for one side of the body with regard to limbs(hand and foot) eyes and ears is of long-standing interest for the

study of cerebral lateralization but also in its own regardHandedness probably the most investigated of these so-calledfunctional lateralizations or asymmetries is indicative of languagelateralization in the brain (Sza1047298arski et al 2002 Sza1047298arski

Holland Schmithorst amp Byars 2006) and is of ubiquitous impor-

tance in every-day life With regard to its distribution it is well-known that right-hand preference is dominant in the populationwith prevalences around 90 (Coren 1993 Peters Reimers amp

Manning 2006)Footedness refers to the dominant or preferred foot when

performing manipulative or mobilizing actions in a bilateral

context (Chapman Chapman amp Allen 1987 Gabbard amp Iteya1996 Sadeghi Allard Prince amp Labelle 2000) like kicking a ball

(skilled movement) or standing on one foot (unskilledstabilizingbalancing movement) Footedness is of importance in sports (egCarey et al 2009) but has also been reported to be an indicator of language and other cerebral lateralizations even superior to

handedness (Chapman et al 1987 Gabbard amp Iteya 1996 Eliasamp Bryden 1998 Elias Bryden amp Bulman-Fleming 1998Searleman 1980 Strauss 1986) probably because of less socialpressure regarding side preference (Chapman et al 1987) Right-

foot preference is considerably lower than right-hand preference

in the population averaging around 80 (Porac amp Coren 1981) butremarkably independent of foot skills (Carey et al 2009)

Eyedness (ocular or sighting dominance) refers to the prefer-

ence of one eye for monocular activities such as looking through atelescope and must be distinguished from sensory dominance inbinocular activities and acuity dominance (visual acuity differ-

ences between the eyes) with both of which it is uncorrelatedwith (Porac amp Coren 1976) Only about two thirds of the popula-tion is right-eyed (Bourassa McManus amp Bryden 1996 Porac ampCoren 1976) Earedness refers to the preference of one ear in

monaural activities such as placing an ear against a closed door tolisten in to a conversation and appears to be the least investigated

Contents lists available at ScienceDirect

journal homepage wwwelseviercomlocateneuropsychologia

Neuropsychologia

httpdxdoiorg101016jneuropsychologia201407027

0028-3932amp 2014 Published by Elsevier Ltd

n Corresponding author Tel thorn43 1 4277 47119 fax thorn43 1 4277 47192

E-mail address ulrichtranunivieacat (US Tran)

Neuropsychologia 62 (2014) 220ndash232



of the lateral preferences that are of concern here (Porac amp Coren1981) Similarly to eyedness sensory dominance or differences inacuity in binaural activities need to be conceptually distinguishedfrom earedness (Noonan amp Axelrod 1981) Earedness is only

weakly functional asymmetric about 60 of the population beingright-eared (Porac amp Coren 1981) but is apparently a betterpredictor of language lateralization than handedness footednessor eyedness (Strauss 1986)

A plethora of studies has provided evidence that overall lateralpreferences in handedness footedness eyedness and earednessare concordantly interrelated with associations between handed-ness and footedness being often strongest (Bourassa et al 1996

Dellatolas Curt Dargent-Pareacute amp De Agostini 1998 Dittmar 2002Kang amp Harris 2000 McManus Porac Bryden amp Boucher 1999Noonan amp Axelrod 1981 Porac 1997 Reiss 1999 Reiss amp Reiss1999 Suar Mandal Misra amp Suman 2007) Thus lateral prefer-

ences may share a common genetic or biological origin primary oroverall sidedness (Annett 2002 Corballis amp Morgan 1978McManus 1985 Previc 1991) While family and genetic studiessuggest (strong) familial aggregations and (weak) genetic associa-

tions (Bourassa et al 1996 Dellatolas et al 1998 McManus et al1999 Reiss 1999 Reiss amp Reiss 1999 Warren Stern DuggiralaDyer amp Almasy 2006) some twin studies have failed to con1047297rmthe genetic determination of sidedness (Reiss Tymnik Koumlgler

Koumlgler amp Reiss 1999) To date a complex multigenetic and multi-factorial model of lateral preferences and their interrelationsappears most likely (McManus Davison amp Armour 2013 Reiss1999 Warren et al 2006)

However research into lateral preferences faces some impor-tant methodological problems First given the skewed distribu-tions of lateral preferences sample size and study power are anissue For example the 1090 handedness ratio lowers the power

of statistical tests by about 50 compared to a 5050 ratio Largesamples are thus required

Second classi1047297cation of lateral preferences frequently adopts either

a dichotomy (rightleft and rightnon-right) or a trichotomy (rightmixedleft) often based on arbitrary criteria and cutoffs on dimen-

sional continuous measures This heterogeneity may prohibit directcomparisons between studies (Beaton 2008) and may also lead to

vastly different results even with the same data (Kelley 2012) Most of the above reviewed studies used dichotomies for classi1047297cation (but seeDittmar (2002) Gabbard and Iteya (1996) and Kang and Harris(2000)) However there is evidence from latent variable analyses that

at least for handedness a trichotomy may be more adequate (Dragovicamp Hammond 2007 Dragovic Milenkovic amp Hammond 2008)

Third with regard to assessment itself the use of multi-iteminventories is recommended The use of single items (such as lsquowriting

handrsquo for handedness) may entail the underestimation of interrela-tions of lateral preferences (Bourassa et al 1996 McManus et al 1999Warren et al 2006) and of associations with other variables such assex (Papadatou-Pastou Martin Munafogravem amp Jones 2008) Yet

existing multi-item inventories like the Edinburgh HandednessInventory (EHI Old1047297eld 1971) and the Lateral Preference Inventory(LPI Coren1993) differ with regard to item composition and responseformat and rigorous psychometric analyses are scarce Existing ana-lyses suggest that some items of widely-used self-report inven-

tories are inappropriate for the accurate assessment of handedness(Dragovic 2004 Dragovic amp Hammond 2007 Milenkovic amp Dragovic2013 Veale 2013) and that skilled and unskilled activities may

constitute separate factors in handedness (Healey Liederman ampGeschwind 1986 Kang amp Harris 2000 Mikheev Mohr AfanasievLandis amp Thut 2002 Nicholls Thomas Loetscher amp Grimshaw2013 Steenhuis amp Bryden 1989) and footedness (Kalaycıoğlu Kara

Atbaşoğlu and Nalccedilacı 2008 Kang amp Harris 2000 Mikheev et al2002 Schneiders et al 2010) However the reported multidimension-

ality of handedness and footedness may have been spurious Studies

relied on factor-analytic methods that were not suited for the highlyskewed item response distributions that are typically encountered inlateral preference inventories This may have resulted in an over-extraction of factors (see Bernstein and Teng (1989)) caused by the

clustering of items with similar distributional properties in differentfactors With regard to response format it is unclear whether threecategories delineating lsquorightrsquo lsquoleftrsquo and lsquono preferencersquo as in the LPI or

1047297ve categories differentiating within lsquoleftrsquo and lsquorightrsquo between lsquoalwaysrsquo

and lsquousually

rsquo as in revised versions of the EHI (Veale 2013) are bettersuited for the assessment of lateral preferences

Overall there is a dearth of psychometric and latent variableanalyses with regard to the assessment and classi1047297cation of self-

reported lateral preferences even though such analyses are of importance for the various and numerous 1047297elds of applied lateralityresearch

Recent studies point out that mixed-handedness may be a risk

factor for neurodevelopmental and neurobehavioral disorders(eg ADHD and language problems Rodriguez et al 2010 schizo-phrenia Dragovic amp Hammond 2005 Sommer Ramsey KahnAleman amp Bouma 2001 schizotypy Somers Sommer Boks amp

Kahn 2009) as mixed-handedness is considered an observablemanifestation of underlying neurodevelopmental instability(Golembo-Smith et al 2012 Rodriguez amp Waldenstroumlm 2008)and de1047297cits in lateralization (Crow 2013) Recently Willems Van

der Haegen Fisher and Francks (2014) have advocated speci1047297callyincluding left-handers in neuroscienti1047297c and neurogenetic studiesinstead of excluding them this would further know-ledge of brain functioning and allow a deeper insight into cerebral

lateralization and its genetic underpinnings as it is currently thecase However there is a need for psychometrically validatedinstruments that can be reliably used in applied research(Rodriguez et al 2010)

The present study addressed the above issues By design ourstudy comprised three independent large samples (total

N 415100) following recent recommendations to counteract

potentially false-positive and thus irreproducible research 1047297nd-ings (Asendorpf et al 2013) In genome-wide association stu-

dies independent discovery and replication samples within thesame study are considered best practice in order to guard

against false-positive 1047297ndings and to demonstrate the robust-ness of an effect if the replication is successful ( McCarthy et al2008) The present study included one sample (n42400) inwhich self-reported handedness was assessed with more items

than in the other two samples (total n412700) This sampleserved for calibration purposes (calibration sample) whereasthe other two samples served for the purpose of cross-validation (comparison sample 1 and 2) With regard to all

other lateral preferences the three samples were full replicationsamples of each other

First we investigated the dimensional structure item proper-ties and optimal number of response categories of widely-used

self-report measures of lateral preferences in handedness footed-ness eyedness and earedness with structural equation modeling(SEM) and item response theory (IRT) Second using two inde-pendent approaches latent class analysis and taxometric analysis

we determined whether lateral preferences were categorical ordimensional providing empirically derived cutoffs that may beused in future research Third interrelations between lateralpreferences were examined investigating evidence for underlying

overall sidedness and also investigating the in1047298uence of sex andage on lateral preferences and sidedness Fourth the observedpairwise associations of lateral preferences were utilized to probepredictions of two speci1047297c single-locus genetic models right shift(RS) theory (Annett 2000 Annett 2002) and the dextral and

chance allele model (DC model McManus 1985) (for background

and details see Section 236 below)

US Tran et al Neuropsychologia 62 (2014) 220ndash 232 221



2 Material and methods

21 Participants

Three independent samples were used in this study one calibration sample

(nfrac142456) and two comparison samples comparison sample 1 (nfrac147658) and

comparison sample 2 (nfrac145062) Descriptive characteristics of the samples aregiven in Table 1 Overall there was a broad age range and slightly more women

than men A majority of the participants in the samples were Austrian or German

Participants with nationalities other than Austrian or German were Italian (12)Turkish (5) and Romanian (3) Samples differed with regard to nationality

( χ 2(4)frac1420434 po 001 more Germans in the calibration sample) and sex ( χ 2(2)frac145097 po 001 more women in the comparison samples) Participants in compar-

ison sample 1 were also on average 55 years younger than participants in the other

two samples (t (15141)frac142351 po 001 dfrac14 38)

22 Procedure and measures

Data were collected by a large number of data collectors in the course of a

larger project on individual difference variables For the three samples waves of

data collection were temporally separated by about half a year (comparison sample

1 vs 2) and one year (comparison sample 2 vs calibration sample) respectively

and independent from each other with regard to the data collectors involved

Participants were approached on a personal basis using word-of-mouth and

personal contacts Participants had to be 1047298uent in German as this was the survey

language Apart from insuf 1047297

cient language pro1047297

ciency there were no furtherexclusion criteria Study participation was voluntary anonymous and participants

were not remunerated for participation Participants completed the questionnairesindependently and unaided

Participants in the calibration sample were presented with the 16 non-

overlapping handedness items of the 10-item EHI (Old1047297eld 1971) and 12-item

LPI (Coren1993) Items asked for hand preference with regard to writing drawing

throwing a ball to hit a target (lsquothrowingrsquo) holding a tennis or squash racket

(lsquotennisrsquo LPI) using a toothbrush (lsquotoothbrushrsquo) using a knife to cut something

without simultaneously using a fork ( lsquoknifersquo) using a hammer to drive a nail into

something (lsquohammerrsquo LPI) striking a match ( lsquomatchrsquo) using a pencil eraser

(lsquoeraserrsquo LPI) dealing a card from a deck of cards ( lsquocardrsquo LPI) threading a needle

(lsquoneedlersquo LPI) holding a 1047298y 1047298ap (lsquo1047298y 1047298aprsquo LPI) using scissors (lsquoscissorsrsquo EHI)holding a spoon (lsquospoonrsquo EHI) the upper hand when holding a broom ( lsquobroomrsquo

EHI) and opening the lid of a box (lsquoboxrsquo EHI) Response options were always right

usually right no preference usually left and always left (in this order) coded thorn2

thorn1 0 1 and 2 respectively Cronbach α of the 16-item scale was 96 94 for the10 EHI items and 96 for the 12 LPI items

Participants in the comparison samples were presented with four of the above16 items (lsquowritingrsquo lsquothrowingrsquo lsquoknifersquo and lsquohammerrsquo) that had been selected

independently and a priori with respect to broad trait coverage (vs redundancy)

item performance indicators and balance of 1047297ne- vs gross-motor skills Response

options were left either and right (in this order) coded 1 0 and thorn1 respectively

Cronbach α of the 4-item scale was 91 in comparison sample 1 and 92 in

comparison sample 2 For ease of presentation options either and no preference are

uniformly referred to as no preference in the remainder of this text

For the assessment of footedness eyedness and earedness the three respectiveself-report scales of Coren (1993) were used Items asked for foot preference with

regard to kicking a ball to hit a target (lsquoballrsquo) picking up a pebble with the toes

(lsquopebblersquo) stepping on a beetle or a cigarette stump ( lsquobeetlersquo) stepping up onto a

chair (lsquochairrsquo) eye preference with regard to looking through a telescope ( lsquotele-

scopersquo) looking into a dark bottle to see how full it is (lsquobottlersquo) peeping through a

keyhole (lsquokeyholersquo) sighting down a gun or ri1047298e (lsquogunrsquo) ear preference with regard

to placing an ear against a closed door to listen in to a conversation going on

behind (lsquodoorrsquo) placing an earphone (lsquoearphonersquo) placing an ear against someones

chest to hear hisher heartbeat (lsquoheartbeatrsquo) placing an ear against a small box to

hear a clock ticking within (lsquoclockrsquo) Items were presented with 1047297ve response

categories in the calibration sample and three response categories in the compar-

ison samples Cronbach α was 817173 for footedness in the calibration and thetwo comparison samples respectively 949090 for eyedness and 877981 for

earedness Lateral preference scales were presented to participants in one block in

the order of handedness footedness eyedness and earedness

23 Statistical analysis

231 Handedness dimensionality and item selection

Dimensionality and item properties were investigated with SEM and IRT

methods with Mplus 611 (Mutheacuten amp Mutheacuten 2008) One-factor models were

1047297tted to the data of the calibration sample using robust weighted least squaresestimation with a mean- and variance-adjusted chi-square test statistic (WLSMV)

which is based on the itemsrsquo polychoric correlation matrix conforming to the

items ordered categorical format and also dealing adequately with the skewed

item response distributions (Beauducel amp Herzberg 2006)

In terms of IRT analysis 1047297tting one-factor models with WLSMV to the data

corresponded to 1047297tting the graded response model (GRM Samejima 1969) to the

data where a persons probability of endorsing a speci1047297c item response category is

modeled by a cumulative function involving the persons latent trait value and a set

of item parameters corresponding to item discrimination and item thresholds the

latter indicating the point on the latent trait continuum where the chance of

endorsing a given or a higher response category is 50 for a person with the samelatent trait value Item discriminations in the GRM correspond to factor loadings in

SEM and may be estimated via SEM alongside threshold parameters Item

parameters were estimated using Mplusrsquo DELTA parameterization and the variance

of the latent trait was set to unity

Model 1047297t was assessed with the comparative 1047297t index (CFI) the Tucker-Lewis

index (TLI CFI and TLI good 1047297t Z 95 acceptable 1047297t Z 90) and the root mean

square error of approximation (RMSEA good 1047297t o 06 acceptable 1047297t o 08) using

the benchmarks of Hu and Bentler (1999) In analyses with few degrees of freedom

(df ) evaluation of model 1047297t was primarily based on CFI and TLI because RMSEA

penalizing for model complexity with the chi-square to df ratio may then be

in1047298ated (Kenny Kaniskan amp McCoach 2014) Based on these analyses items were

selected that loaded highest on the latent trait and were kept for further analysis

232 Handedness number of response categories

Item characteristic curves (ICCs) of the retained items in the calibration sample

were inspected with regard to whether response categories were suf 1047297ciently

separated Being based on a cumulative response function threshold parametersin the GRM are by de1047297nition in the same order as the response categories and

convey no information on category separation ie whether each category hashighest probability of endorsement along a distinct section of the latent trait that

does not overlap with sections of the other categories Indication of insuf 1047297cient

separation may however be gained from inspection of the ICCs Informed by theseanalyses the number of response categories was reduced combining adjacent

response categories and assessing the 1047297t of some alternative models in the

calibration sample The best-1047297tting alternative was kept as 1047297nal model and also

investigated in a 4-item short scale which was also used in the comparison

samples Fit of one-factor models in this scale was then further assessed in the

comparison samples

233 Handedness latent classes and taxonity

Based on the 1047297nally obtained scale (calibration sample) and the 4-item short scale

(comparison sample 1 and 2) we determined whether the latent trait underlying

handedness was categorical or continuous with latent class analysis (LCA eg Collins

and Lanza (2010)) and taxometric analysis (Meehl 2004 Waller amp Meehl 1998)independently in the calibration sample and the two comparison samples In addition

analyses with the 4-item short scale were also performed in the calibration sample to

enable direct comparisons with results in the two comparison samples LCA employs a

latent variable model wherein associations between observed variables are explained by

a number of underlying discrete classes given the latent classes associations between

the observed variables disappear (conditional independence) Conditional independence

may be unrealistic in certain cases and can be relaxed allowing also for residual

dependence of observed variables LCA has been utilized in studies on handedness

before (Dragovic amp Hammond 2007 Merni Di Michele amp Soffritti 2013) We evaluatedthe 1047297t of models with increasing numbers of latent classes determining the smallest

number that explained the data best Latent GOLD 45 was utilized for these analyses

treating items as nominal following previous results (Dragovic amp Hammond 2007

Dragovic et al 2008) Model 1047297t was assessed with (1) the Bayesian information criterion

(BIC) based on the log-likelihood value of the model (2) percentages of classi1047297cation

error (3) the likelihood-ratio goodness of 1047297t statistic (L2) Indicator loadings ie

standardized linear regression coef 1047297cients for the indicatorndashcluster relationships are

also reported

Table 1

Sample characteristics

Sample

Calibration Comparison 1 Comparison 2

n 2455 7658 5062

Women n () 1240 (507)a 4456 (582) 2749 (543)

Ag e range ( years) 18ndash90b 18ndash89 18ndash92

Interquartile range 23ndash48b 22ndash35 22ndash48Mean (SD) 3564 (1548)b 3024 (1262) 3574 (1605)

Nationality n ()c

Austria 1397 (573) 5339 (700) 3415 (677)

Germany 923 (378) 1773 (232) 1310 (260)

Other 119 (49) 514 (67) 316 (63)

a nfrac142448 due to missing datab nfrac142423 due to missing datac

nfrac142439 7626 and 5041 due to missing data

US Tran et al Neuropsychologia 62 (2014) 220ndash 232222



Taxometric analysis served to cross-validate the LCA solutions providing an

alternative approach to assess the latent structure of handedness and relying on fewer

assumptions than LCA Like LCA taxometric analysis has been utilized in studies on

handedness before (Dragovic et al 2008) Taxometric analysis divides observed

variables into input and output indicators creates a series of ordered subsamples along

the input indicator and graphs the results MAMBAC analysis (mean-above-minus-

mean-below-a-cut Meehl amp Yonce 1994) one of the most often used taxometricmethods (Haslam Holland amp Kuppens 2012) was used in this study utilizing TaxProg

(Ruscio 2012) MAMBAC sorts cases along the input indicator ( x-axis) and plots at

evenly spaced cuts mean differences on the output indicator ( y-axis) Mean differences

are calculated as means for cases above the cut minus means for cases below the cutCategorical data should yield a peaked curve whereas dimensional data are expected to

yield a concave curve (Meehl amp Yonce 1994) TaxProg uses the observed variables in all

possible inputndashoutput pairings and 50 cuts as default It also allows the generation of

categorical and dimensional comparison data (kfrac14100 samples each with size

nfrac14100000 each as default) With the comparison data a quantitative index of curve

1047297t (comparison curve 1047297t index [CCFI] Ruscio amp Kaczetow 2009 Ruscio WaltersMarcus amp Kaczetow 2010) may be obtained ranging from 0 (dimensional) to 1

(categorical) For 4oCCFIo6 results are inconclusive and should be interpreted with

caution CCFI values have been found to be highly reliable in differentiating betweendimensional and taxonic simulated data even under unfavorable conditions (Ruscio amp

Kaczetow 2009 Ruscio et al 2010) and use of CCFI values also reduced spurious

1047297ndings in real data (Haslam et al 2012) Evaluation of taxonity was therefore strictly

based on CCFI values

Differences between obtained handedness classestaxa were investigated (analysis

of variance ANOVA) also with respect to laterality quotients (LQs) that are commonly

used with the EHI computed for each scale and domain with the formula (Kelley 2012)

LQ frac14sumk j frac14 1score of ith item

sumk j frac14 1absolute score of ith itemthorn2 number of items scored 0

100

where k refers to the number of items in the scale LQ scores ranging from 100

(exclusive left preference) to thorn100 (exclusive right preference) were further used

to derive cutoffs of obtained classestaxa in all laterality domains with nonpara-

metric receiver-operator-curve (ROC) analyses

234 Footedness eyedness earedness

Similar analyses as for handedness were conducted with regard to scales of

footedness eyedness and earedness Associations between lateral preferences in

all four investigated domains and with sex and age were then investigated with

multinomial logistic regression analyses controlling for sample and interactions of

sample with main effects to test for replicability of effects

Cases with missing values in any items of the laterality scales were included inall SEM and LCA analyses but due to methodological limitations only cases with

complete data could be included in the taxometric analyses More than 995 of

participants had none or at most one missing value per sample and scale

235 Sidedness

The overall underlying structure of lateral preferences sidedness was 1047297nally

investigated with LCA Associations of sidedness with sex and age and associations

of the occurrence of inconsistent (ie not absolutely concordant preferences in any

pair of domains) and crossed (ie a right preference in one domain and a leftpreference in another) lateral preferences in the four domains with sex age and

sidedness were investigated with (multinomial) logistic regression analyses again

testing for replicability

236 Probing predictions of single-locus genetic models

RS theory (Annett 2002) assumes a continuum from left to right preferences andasserts that lateral preferences are associated with cerebral dominance A persons

position on the leftndashright continuum depends on a purely stochastic process assuming

an underlying normal distribution but is affected by a hypothesized RS-allele Presence

of one allele (genotype RSthorn) causes a right shift presence of two alleles (RSthornthorn) afurther right shift compared to individuals with RS genotype Annett (2000)

presented a statistical model to predict the bivariate distribution of lateral preferences

according to RS theory using a dichotomous classi1047297cation of right vs left preferences A

Supplementary table in Annett (2000) contains empirical estimates of the shift

introduced by the RS-allele and of the population proportions of RS RSthorn and

RSthornthorn genotypes valid for Western populations In the present study we investigated

the 1047297t of predicted proportions of all pairs of lateral preferences in our data with chi

squared goodness-of-1047297t tests

The DC model (McManus 1985) posits that left and right lateral preferences dependon Dextral (D) and Chance (C) alleles Genotype DD has a 0 probability for left

preferences DC 25 and CC 50 In contrast to the RS model the DC model does not

allow for mixed preferences (which may be combined with either left or right

preferences in the RS model) but excludes them from computations A speci1047297c

prediction of the DC model is that for pairs of lateral preferences the proportions of

rightndashleft preferences and leftndashright preferences are the same (see Annett 2000)

McManus et al (1999) found that this equality held in groups of consistent-handers

(who use the same hand for writing and throwing) and inconsistent-handers separately

We derived the respective proportions for all pairs of lateral preferences in our data and

investigated whether their con1047297dence intervals overlapped

3 Results


A one-factor model and the graded response model yielded a good

1047297t to the data (Table 2) Yet lsquowritingrsquo and lsquodrawingrsquo were highlyredundant (r frac14 99) and four other items (match card needle broom

and box) had standardized loadings o90 while the rest displayedloadings 490 (Table 3) Excluding these redundant and least 1047297tting

1047297ve items increased the model 1047297t (Table 2) The remaining 10 itemswere retained for further analysis


Item thresholds distinguishing overall less frequently endorsedresponse categories from exclusive right-handedness all lay in thenegative latent trait spectrum (ranging from 158 to 60 in the

DELTA parameterization) and appeared crowded (mean distancebetween thresholds 22) Inspection of ICCs (Fig S1) revealed that

the response curves of the three middle categories (usually left no

preference and usually right ) overlapped substantially indicating that

these categories were insuf 1047297ciently separated from one another andthat they were also insuf 1047297ciently separated from the extremecategories in all retained items with the exception of usually right

in all items save lsquowritingrsquo and of no preference in lsquo1047298y 1047298aprsquo

Three alternatives were tested with regard to the combination of response categories combining (a) always left and usually left scoringthem both as 1frac14left (b) usually left no preference and usually right scoring them as 0frac14no [exclusive] preference considering usually left

and usually right preferences to indicate no exclusive preferences and(c) always left and usually left scoring them as 1frac14left and always

right and usually right scoring them as thorn1frac14right Alternative(c) yielded the best model 1047297t especially improving the RMSEA value

(Table 2) and further increasing the already high item factor loadings(Table 3) However according to ICCs (not shown) no preference wasonly in lsquo1047298y 1047298aprsquo the most likely category in a distinct section of thelatent trait Yet with regard to the scoring of the LQ and the LPI that

incorporate in both cases a middle category this solution still appearedtenable and of heuristic value All remaining analyses in the calibrationsample data were thus based on scoring three response categoriescombining always left and usually left and always right and usually

right

33 Handedness latent class and taxometric analyses

331 Calibration sample

Latent class analysis initially suggested four handedness classes

in the calibration sample (Table 4) Class 1 (class size 843)pertained to exclusive right-handers Class 2 (035) to mixed-handers Class 3 (072) to left-handers and Class 4 (inconsistentright-handers 051) to persons in-between Classes 1 and 2

preferring less exclusively the right hand than members of Class1 Clusters differed signi1047297cantly in LQ scores (right-handers

M frac149779 SDfrac14634 inconsistent right-handers M frac145422

SDfrac141535 mixed-handers M frac141339 SDfrac142808 left-handers

M frac148167 SDfrac141987 F (3 2451)frac141927892 po 001 po001for all pairwise comparisons) with class explaining 959 of totalscore variance

MAMBAC analysis (using default settings) in the total sample

suggested that overall raw scores represented a categoricalrather than a dimensional trait CCFIfrac14 69 In order to investigate

whether there were more than two taxa (as indicated by LCA)




across the spectrum of handedness scores MAMBAC analyseswere applied to subsamples that contained two or more adjacentlatent classes In order to be able to detect taxonity of smallclasses taxon base rates (derived from LCA) were supplied as input

and the number of cases to be set aside at each extreme along theinput indicator before making the 1047297rst and last cut was set to 10(defaultfrac1425)

In the 4-cluster solution differences between right-handers

and inconsistent right-handers appeared to be not clearly taxonicCCFIfrac14 50 However adding mixed-handers to the analysis sampleyielded evidence of taxonity CCFIfrac14 63 Taxonity was also clearlypresent in the subsample of left- and mixed-handers CCFIfrac14 75

In the 3-cluster solution fusing inconsistent right-handers withmixed-handers MAMBAC analyses corroborated taxonity of allthree classes (Table 5) The 3-cluster solution was therefore kept asthe 1047297nal model Class sizes and response probabilities are provided

in Table 5 along with LQ cutoffs Indicator loadings ranged from73 (spoon) to 90 (hammer) with a mean of 79 Notably loadingsof lsquothrowingrsquo (83) lsquotennisrsquo (80) lsquoknifersquo (80) and lsquohammerrsquo werehighest overall all remaining loadings being o 80 Mean differ-

ences in LQ scores were large (right-handers M frac149777 SDfrac14633inconsistent right-handersmixed-handers M frac144254 SDfrac142364left-handers M frac147594 SDfrac142644 F (2 2452)frac142193348

po 001 po 001 for all pairwise comparisons) with class explain-

ing 947 of total score variance Among right-handers right-handpreference was practically exclusive (see response probabilities inTable 5) Inconsistent right-handersmixed-handers had a highermean LQ score than mixed-handers in the 4-cluster solution and

had a relative right-hand preference across all indicators (seeresponse probabilities in Table 5) Left-handers had also a sub-stantial probability of right-hand preference in lsquowritingrsquo andshowed otherwise less exclusive hand preference than right-

handersCross-validation with the 4-item short form in the calibration

sample corroborated a 3-cluster solution (Table 5 detailed LCA 1047297t

statistics omitted for brevity) However based on four itemspersons previously classi1047297ed as inconsistent right-handers

mixed-handers were more often classi1047297ed as right-handed andthe pattern of hand preference in the remaining class was more

indicative of mixed-handedness than mere inconsistent right-handedness with probability of no preference in lsquohammerrsquo noweven slightly higher than for right (Table 5) However mixed-handers still had a relative or substantial right-hand preference in

most of the tasks Indicator loadings were 76 (writing) 85(throwing) 80 (knife) and 93 (hammer) Mean differences inLQ scores were again large (right-handers M frac149777 SDfrac141004mixed-handers M frac14547 SDfrac142651 left-handers M frac147523

SDfrac143173 F (2 2452)frac141547286 po 001 po001 for all pair-wise comparisons) with class explaining 927 of total scorevariance Cutoffs in the 4-item solution were approximatelysymmetric across the LQ continuum (Table 5) Moreover whereas

in the 10-item solution right-handers endorsed no preference up totwo times and left-handers up to four times (91 of right- and 78of left-handers not endorsing no preference) these numbers werereduced to one each in the 4-item solution with 98 of right- and

99 of left-handers not endorsing no preference In return mixed-handers were characterized by endorsing with high probability(87 of mixed-handers) at least once no preference Apparentlyclassi1047297cation of handedness was thus more stringent in the 4-item

solution It was therefore used for all ensuing analyses

332 Comparison samples

One-factor models 1047297tted the data of the comparison sampleswell (Table S1) 3-cluster solutions also proved the best 1047297ttingmodels in the two comparison samples (detailed LCA 1047297t statistics

omitted for brevity) clearly corroborated by MAMBAC analyses aswell (Table 5) Class sizes and obtained cutoffs were in goodaccordance between samples and with results of the 4-item short

form in the calibration sample Response probabilities agreed well

across the comparison samples and were also broadly comparable

Table 2

Fit of one-factor models (calibration sample)

χ 2 (df ) CFI TLI RMSEA [90 CI]

Handedness 1047297ve response categories

16 items 85215 (104) 994 993 054 [051058]

10 items 28141 (35) 998 997 054 [048059]

Handedness combining response categories (10-item measure)

(a) always left and usually left 24627 (35) 998 997 050 [044056]

(b) usually left no preference and usually right 23413 (35) 998 997 048 [042054](c) always left and usually left and always right and usually right 16246 (35) 999 999 039 [033045]

Short measures combining response categories as in (c)

Handedness (4-item short form) 2266 (3)a 1000 999 052 [033072]

Footedness 473 (2) 999 998 024 [000052]

Eyedness 1949 (2) 1000 999 060 [037085]

Earedness 7331 (2) 994 982 121 [098145]

excluding lsquoheadphonersquo 1035 (1)b 999 997 062 [032098]

Note Constraining factor loadings of items alsquothrowingrsquo and lsquohammerrsquo b lsquoheartbeatrsquo and lsquoclockrsquo to equality to attain convergence

Table 3

Handedness standardized factor loadings (calibration sample)

Item Five response categories Three response categories

16 items 10 items 10 items 4 items

Writing 95 94 96 95

Drawing 96

Throwing 93 94 98 99n

Tennis 94 94 98

Toothbrush 91 91 96

Knife 92 92 96 97

Hammer 98 98 99 99n

Match 88

Eraser 93 93 96Card 80

Needle 69

Fly 1047298ap 93 93 97

Scissors 92 92 97

Spoon 91 91 95

Broom 68

Box 78

Note Items retained in item selection printed boldface Items of the 4-item short

form are underlinedn Factor loadings constrained to equality




to those of the calibration sample (Table 5) Indicator loadings inthe comparison samples compared to the calibration sample(writing 7774 throwing 7781 knife 7779 and hammer8587) However mixed-handers in the comparison samples had

higher response probabilities for no preference than in the calibra-tion sample Using originally three instead of 1047297ve categoriesapparently entailed a more frequent endorsement of no preference

among mixed-handers Accordingly 100 of mixed-handers in the

comparison samples endorsed at least once no preference whereasright- and left-handers at most once (overall 96 of right- and 90of left-handers not endorsing the middle category)

34 Footedness eyedness earedness calibration sample

One-factor models combining always left and usually left as well as

always right and usually right 1047297tted the data well (Table 2) againbetter than when utilizing all 1047297ve response categories (not shown)

However factor loadings of some items were relatively low (lsquochairrsquo infootedness Table 6 lsquoheadphonersquo in earedness 73) Excluding lsquochairrsquodid not raise model 1047297t (not shown) hence this item was kept in thefootedness scale Excluding lsquoheadphonersquo did raise model1047297t (Table 2)it

was therefore excluded from the earedness scaleLCA provided evidence of 3-cluster solutions each for footed-

ness eyedness and earedness (detailed LCA 1047297t statistics omittedfor brevity) consisting each of rightleft- and mixed-preference

classes (Table 6) Notably size of right-preference classes wasconsiderably smaller than in handedness and mixed-preferenceclasses were large in footedness and earedness Preference classesin all domains were characterized by a consistent endorsement of

preferred side (no preference in the mixed-preference classes) withhighest probability across all respective indicators (see responseprobabilities in Table 6) Exceptions to this occurred in lsquoballrsquo infootedness and lsquogunrsquo in eyedness mixed-footed respondents had astrong right-foot preference in lsquoballrsquo and mixed-eyed respondents

a right-eye preference in lsquogunrsquo Note however that class member-ship in footedness and eyedness depended less on items lsquoballrsquo and

lsquogunrsquo than on the remaining items in the respective scales (see

indicator loadings in Table 6) lsquoChairrsquo had also a low indicatorloading in footedness however excluding this item did not

substantially alter the cluster solutionOtherwise mixed-preference classes were again clearly distinct

from right- and left-preference classes across all three domains

regarding the use of the no preference option 100 of respondentsof mixed-preference classes endorsed no preference at least onceper scale whereas respondents of right-preference classes at mostonce and respondents of left-preference classes at most twice

(73 84 and 79 of right- and 51 76 and 82 of left-preference respondents not endorsing no preference in footednesseyedness and earedness respectively)

35 Footedness eyedness earedness comparison samples

One-factor models also 1047297tted the data in the comparison samples

well (Table S1) Again 3-cluster solutions could be replicated and

were also clearly corroborated by MAMBAC analyses (Table 6) Classsizes response probabilities and cutoffs were all in good accordancebetween samples mixed preference classes were however consis-tently larger in comparison sample 1 than in the other two samples

One hundred percent of respondents of mixed-preference classesendorsed no preference at least once per scale whereas respondentsof right-preference classes at most once and respondents of left-preference classes at most twice (overall 74 83 and 77 of right-

and 53 78 and 80 of left-preference respondents not endorsingno preference in footedness eyedness and earedness respectively)

36 Associations between lateral preferences

Table 7 presents results on handedness and Table 8 on footed-ness eyedness and earedness For each of the models sample wasincluded as a main effect to control for differences in preference

proportions across samples Furthermore stability and replicabil-ity of main effects was checked by testing interactions of samplewith each of the signi1047297cant main effects combining mixed- and

left-handed in analyses on footedness eyedness and earedness inorder to avoid numerical problems in estimation Interaction termswere eliminated with a stepwise backwards procedure keeping in

1047297nal models only terms that were signi1047297cant at po 05 With

regard to interpretation we focus mostly on effects that could beestimated with highest precision and reliability ( po001) and that

were replicable across samples (ie were not quali1047297ed by sampleinteractions and absent in some of the samples) Overall regres-

sion models explained sizable proportions of the lateral preferencedistributions (pseudo R2 values in Tables 7 and 8)

Handedness (Table 7) showed largest associations with footed-ness and small associations with eyedness smallest with ear-

edness with associations being mostly concordant Earedness (leftpreference) was reliably associated only with left-handednessNotably men had overall a slightly higher left-hand preferencethan women however this effect was only small and not stable

across samplesPreferences for footedness eyedness and earedness (Table 8)

were again mostly concordant across the various domains of laterality Overall handedness was a stronger predictor of footed-

ness than for eyedness or earedness Footedness and handednesswere equally predictive of eyedness In earedness footedness wasa stronger predictor than handedness Mixed preferences infootedness eyedness and earedness were more frequent in

younger participants and left-earedness was more frequent inolder participants Moreover men had more often mixed and leftpreferences in footedness and earedness than women whereaswomen were more often left-eyed than men

37 Sidedness

Classes of lateral preference served as indicators in this analy-

sis Table 9 displays 1047297ts of different cluster solutions Table 10results of the 1047297nal 3-cluster solution The three samples were

collapsed as individual results differed only negligibly from each

Table 4

Handedness 1047297t of latent class models (calibration sample)

Model LL Npar BIC(LL) L2 df p Classi1047297cation error

1-cluster 965553 20 1946717 1136547 2434 o 001 002-cluster 530052 41 1092107 265545 2413 o 001 17

3-cluster 486644 62 1021682 178731 2394 1000 164

4-cluster 476613 83 1018012 158667 2371 1000 191

5-cluster 471353 104 1023883 148146 2350 1000 240

Note LLfrac14log-likelihood Nparfrac14number of parameters BIC(LL)frac14Bayes information criterion based on LL L2frac14likelihood ratio test statistic Retained solution printed

boldface




other A 3-cluster solution 1047297tted the data best but residualdependencies of eyedness and earedness (bivariateresidualfrac144587 in the initial 3-cluster model) and of handednessand footedness (residualfrac141137 after allowing for eyednessndashear-

edness dependence) needed to be allowed for (all bivariateresiduals r126 in the 1047297nal model) indicating that associations

between these domains could not be fully explained by overallsidedness

Around 60 of respondents were classi1047297ed as right-siders 30as mixed-siders and slightly less than 10 as left-siders According

to indicator loadings (handedness 57 footedness 94 eyedness28 earedness 31) and also suggested by response probabilities

Table 5

Handedness class sizes and response probabilities in the latent class model CCFI Values and LQ Cutoffs

Calibration sample Comparison sample 1n Comparison sample 2n

Right Mixed Left Right Mixed Left Right Mixed Left

Class size 849 071 079900n 021n 078n 895 028 077 890 026 084

CCFI 66 76

59n 76n 67 87 88 63LQ cutoffs 472 72 to 7 o7

441n 41 to 40n o40n 441 41 to 40 o40 441 41 to 40 o40

Writing 0 00 099 170281 720028

010099n 330660n 720028n 010099 132166 80 0119 010099 242056 740225

Thr owing 00 0099 131473 890209

010199n 223741n 920108n 010298 095536 83 0413 010198 145036 870311

Tennis 000199 121770 910504

Toothbrush 000198 152957 900307Knife 010099 141472 910108

010198n 362538n 900010n 010197 136225 83 0313 010198 124841 830413Hammer 0 00 099 091180 970103

000099n 303733n 970003n 000199 095933 91 0306 000199 095833 920206

Eraser 000298 204139 880408

Fly 1047298ap 000297 054747 851103

Scissors 0 00 099 082072 830215

Spoon 000298 172359 830511

n Utilizing the 4-item short form Response probabilities pertain to leftnoright preferences CCFI values pertain to tests of right- vs mixed-handers and mixed- vs left-

handers respectively LQ scores were computed with 10 (calibrations sample) and four items (calibration and comparison samples) and a scoring scheme based on three

response categories (see text) Cutoffs were derived with nonparametric ROC analyses (area under the curve [AUCs] Z 957 po 001) maximizing sensitivity and speci1047297city

rounding to the nearest integer Responses with highest probability per class printed boldface

Table 6

Footedness eyedness earedness class sizes and response probabilities in the latent class model CCFI Values and LQ Cutoffs

Scale Calibration sample Comparison sample 1 Comparison sample 2


Footedness

Class size 632 261 106 566 347 086 595 314 091

CCFI 76 87 78 85 77 76

LQ cutoffs 441 41to 16 o16 441 41 to 16 o16 441 41 to 16 o16

Ball (8460) 010298 051976 680923 010297 042769 651323 010297 052669 700822

Pebble (8466) 011089 027227 711811 030592 027027 731908 030592 046730 781309

Be etle ( 83 66) 01 0891 007228 553015 031186 017921 533116 021187 018019 572816Chair (67 51) 08 0884 105139 691516 110980 095537 711515 110782 095437 721315

Eyedness

Class size 630 141 229 567 211 220 572 201 227

CCFI 79 81 72 89 76 84

LQ cutoffs 441 41 to 16 o16 441 41 to 16 o16 441 41 to 16 o16Telescope (9479) 010594 057223 85 0905 020693 057223 820810 010594 087122 830511

Bo ttle (95 82) 01 0693 048313 86 0806 020692 038413 86 0707 020692 048412 831007

Keyhole (9684) 010495 048016 88 0606 020692 047719 85 0708 020494 047719 870607

Gun (9070) 030394 113356 800614 030295 094050 760618 030295 113851 770519

Earedness

Class size 517 286 197 471 315 214 498 286 216

CCFI 79 85 82 85 85 79

LQ cutoffs 426 26 to 26 o26 426 26 to 26 o26 426 26 to 26 o26Door (8167) 0 41086 067320 741214 081083 077518 701020 060883 087318 740917

Heartbeat (90n 76) 030989 048115 83 0909 050986 048214 801010 040888 058213 830809

Clock (90n81) 030394 087418 92 0206 030592 068014 89 0506 030493 077914 880606

Note Numbers in parentheses pertain to factor loadings (SEM) and indicator loadings (LCA) in the calibration sample Response probabilities pertain to leftnoright

preferences CCFI values pertain to tests of right- vs no preference and no vs left-preference respectively LQ scores were computed with four (three in earedness) items per

scale and a scoring scheme based on three response categories (see text) Cutoffs were derived with nonparametric ROC analyses (area under the curve [AUCs] Z 944

po 001) maximizing sensitivity and speci1047297city rounding to the nearest integer Responses with highest probability per class printed boldfacen

Factor loadings constrained to equality




(Table 10) footedness rather than handedness discriminatedmost strongly between sidedness classes Right-handedness wasstrongly favored among both right- and mixed-siders but also wasprominent among left-siders Earedness overall was more con-

cordant with sidedness than eyedness mixed-siders were morelikely right- than mixed-eyed Thus whereas right- and left-siderswere consistently characterized across all four domains withhighest probability by right and left preferences respectively

mixed-siders were with the highest probability mixed-footedand mixed-eared but right-handed and right-eyedSidedness was dependent on sex (multinomial logistic regres-

sion analysis controlling for sample and possible interactions of

sample with main effects with a stepwise backwards procedure asabove overall χ 2(8)frac1426227 po 001 Nagelkerke R2

frac14 021) withhigher proportions of mixed- (ORfrac14128 [119 138] po001) andleft-siders (ORfrac14134 [119 152] po 001) among men than

women Moreover mixed-siders were also younger than bothright- (ORfrac14 98 [98 99] po 001) and left-siders (ORfrac14 99 [9899] po 001)

Probability means (Table 10) show that among right-handers a

substantial proportion was not right-sided 30 being mixed- and3 left-sided Proportions of non-left-siders among left-handers(20 mixed- and 12 right-sided) and non-mixed-siders amongmixed-handers (19 right- and 8 left-sided) were also strikingly

similar around 30 each Within the three handedness classesconsistency with sidedness was thus similar despite vastly differ-ent handedness rates A majority (450) of left-eyed and left-eared respondents was right-sided and 24 and 20 of right-eyed

and right-eared respondents respectively were mixed-sidedOverall inconsistencies in any pair of lateral preferences affected

692 of respondents most frequent in handndashear preferences (478)and least frequent in handndashfoot preferences (329) Inconsistencies

were more frequent (logistic regression analysis but otherwise asabove overall χ 2(6)frac14326429 po001 Nagelkerke R2

frac14 273) inyounger respondents (ORfrac14 99 [99 99] po001) and compared

to right-siders in mixed-siders (ORfrac143204 [2629 3905] po001)and left-siders (ORfrac14218 [190 249] po001) Crossed preferences

affected in total 329 of respondents most frequent in handndasheyepreferences (191) and least frequent in handndashfoot preferences

(46) Excluding mixed-siders crossed preferences (logistic regres-sion analysis as above overall χ 2(5)frac1422865 po001 Nagelkerke

R2frac14 029) were slightly more frequent in men than women (ORfrac14109

[100 118] pfrac14 048) and more frequent in left- than right-siders

(ORfrac14243 [215 275] po001)

38 Single-locus genetic models

Table 11 lists the observed and predicted proportions asderived from RS theory (Annett 2000) of the combinations of

left and non-left preferences (combining mixed and right prefer-ences) for all pairs of lateral preferences collapsing all threesamples The results were noticeably consistent with the predic-tions of RS theory (predicted proportions deviated from observed

proportions mostly by o1) and also supported Annetts notion of a lsquopull to concordancersquo (ie combinations of lateral preferenceswere more often concordant than discordant as predicted by themodel) with regard to handndashfoot preferences Due to the large

sample size some goodness-of-1047297t tests were nominally signi1047297cantHowever deviations of predicted from observed proportions weremostly small Applying the 13-rule (ie adding one-thirds of thepredicted proportions of the discordant combinations to the

respective proportions of the two concordant combinations eachAnnett 2000) did not suf 1047297ciently improve the model 1047297t withregard to handndashfoot preferences (Table 11) Apparently the 13-rule overcorrected the discordant combinations thus yielding

predicted values that were too low However applying an explora-tory 14-rule suf 1047297ciently improved the model 1047297t The observedgood 1047297t of the predictions of RS theory with the data depended oncombining mixed preferences with right preferences Combining

mixed and left preferences data 1047297t was substantially lowered(details omitted for brevity)

In contrast predictions of the DC model (McManus 1985) werenot supported by the data Excluding subjects with mixed pre-

ferences as required by the DC model the predicted equality of proportions of rightndashleft and leftndashright preferences was discon-

1047297rmed for every single pair of lateral preferences (handndashfoot 47[44ndash52] vs 19 [16ndash22] handndasheye 219 [211ndash226] vs

23 [20ndash25] handndashear 270 [261ndash279] vs 27 [24ndash30]footndasheye 201 [193ndash209] vs 40 [36ndash44] footndashear 226[217ndash235] vs 36 [32ndash40] eyendashear 173 [165ndash181] vs

143 [136ndash151])

4 Discussion

Using three independent large samples and applying a variety of latent variable analyses a number of replicable results were obtainedas discussed point-by-point in the following

Table 7

Handedness multinomial regression analysis (nfrac1415139)

Variable Mixed Left

Sex (male) 90 [60 133] 136 [106 174]na

Age 100 [99 101] 100 [100 101]

Mixed-footed 956 [678 1349]nnn 302 [248 367]nnn

Left-footed 1932 [1267 2946]nnn 4259 [3520 5153]nnn

Mixed-eyed 286 [218 375]nnn 187 [151 231]nnn

Left-eyed 212 [156 289]nnn 448 [377 532]nnn

Mixed-eared 140 [107 184]n 133 [110 161]nn

Left-eared 126 [90 175] 174 [145 209]nnn

Model 1047297t χ 2(df ) Nagelkerke R2 357418 (22) po 001 392

Note Using lsquoright-handed rsquo as common comparator for outcome and lsquoright preferencersquo as common

comparator for predictors of lateral preference Effect estimates with highest precision and reliability( po 001) are printed boldface Main effects of and interactions with sample were controlled in the

analyses (not shown)a With regard to sample interactions the effect was absent in the calibration sample and

comparison sample 1 (ORfrac14 93 [77 113])




41 Assessment

Results corroborated that widely-used self-report measures of lateral preferences contain items that distort assessment and

therefore need to be excluded (Dragovic 2004 Dragovic ampHammond 2007 Milenkovic amp Dragovic 2013 Veale 2013)Furthermore SEM and IRT analyses suggested that three responsecategories as in the LPI consisting of lsquorightrsquo lsquoleftrsquo and lsquono

preferencersquo are suf 1047297cient for the assessment of lateral preferencesFurther differentiating within lsquorightrsquo and lsquoleftrsquo options did not

increase the quality of assessmentWe strongly encourage the rigorous psychometric testing of lateral

preference scales and the use of psychometrically validated self-reportquestionnaires in applied research Re1047297ned lateral preference scales

developed here may be utilized as is in future research Howeverresults indicated that there is potential for further improvement eg abimanual task (lsquohammerrsquo) proved to be the most informative indicatorfor handedness Bimanual tasks have already been assumed before to

confer a higher reliability to classi1047297cation (Papadatou-Pastou et al2008) However it may require tasks that need accuracy and which

Table 9

Sidedness 1047297t of latent class models (collapsing all three samples)


1-cluster 4933925 8 9875552 860201 72 o 001 00

2-cluster 4687699 17 9391764 367749 63 o 001 846

3-cluster 4537554 26 9100139 67459 54 o 001 1304

thornresidual eyendashear dependence 4520860 30 9070602 34071 50 o 001 900

thornresidual handndashfoot dependence 4513342 34 9059418 19036 46 o 001 351

4-cluster 4520011 35 9073717 32372 45 o 001 2174

Note LLfrac14log-likelihood Nparfrac14number of parameters BIC(LL)frac14Bayes information criterion based on LL L2frac14 likelihood ratio test statistic Retained solution printed

boldface

Table 10

Sidedness class sizes response probabilities and probability means in the latent class model (collapsing all three samples)

Response probabilities of preferences within sidedness classes Probability means of sidedness within preference classes

Right Mixed Left Right Mixed Left

Class size 610 303 088

Handedness 010098 050589 620533 033067 087319 682012

Footedness 010099 009406 890605 010397 009802 910009

Eyedness 201268 183546 591525 042472 075538 232453

Earedness 18 1963 155233 532423 042076 075340 232354

Note Response probabilities pertain to leftnoright preferences within sidedness classes probability means to proportions of leftmixedright sidedness within preference

classes

Table 8

Footedness eyedness earedness multinomial regression analyses (nfrac1415139 each)

Variable Footedness Eyedness Earedness

Mixed Left Mixed Left Mixed Left

Sex (male) 125 [115 135]nnn 143 [123 165]nnn 91 [83 99]n 82 [75 89]nnn 121 [111 131]nnn 119 [108 130]nnn

Age 99 [99 99]nnn 100 [99 100] 99 [99 100]nnn 99 [99 100]nn 99 [98 99]nnn 101 [100 101]nnn

Mixed-handed 974 [689 1377]nnn 1977 [1297 3014]nnn 282 [214 372]nnn 209 [153

285]nnn137 [104 181]n 127 [91 177]

Left-handed 304 [250 370]nnn 4308 [3560

5213]nnn187 [151 231]nnn 449 [378

533]nnn140 [116 169]nnn 175 [146 211]nnn

Mixed-footed 265 [240 292]nnn

122 [110 135]nnn

365 [334 398]nnn

156 [140 174]nnn

Left-footed 181 [147 225]nnn 244 [207

289]nnn201 [166 243]nnn 349 [293

415]nnn

Mixed-eyed 266 [241 293]nnn 177 [142 219]nnn 330 [298 365]nnn 134 [117 154]nnn

Left-eyed 123 [111 136]nnn 246 [208 290]nnn 117 [105 131]nn 257 [232

284]nnn

Mixed-eared 398 [354 447]nnna 264 [205 341]nnnb 351 [299 412]nnn 99 [82 119]c

Left-eared 156 [140 174]nnn 350 [294 417]nnn 135 [118 155]nnn 256 [231

284]nnn

Model 1047297t χ 2(df ) Nagelkerke

R2

537332 (22) po 001

363

323077 (22) po 001

224

328511 (20) po 001

224

Note Using lsquoright preferencersquo as common comparator for outcomes and predictors of lateral preference Effect estimates with highest precision and reliability ( po 001) that

were also replicable across samples are printed boldface Main effects of and interactions with sample were controlled in the analyses (not shown) With regard to sample

interactions main effects werea Smaller in the calibration sample and comparison sample 2 (ORfrac14347 95 CIfrac14[305 394])b Smaller in the calibration sample and comparison sample 2 (ORfrac14141 [108 183])c Present in the calibration sample and comparison sample 1 (ORfrac14129 [112 146])




may entail negative or hurtful consequences to the performing subjectif wrongly executed lsquoHammerrsquo was previously reported to bestdistinguish left- from right-handers (see Annett (2002) p 35ndash37)correlating more strongly with hand preference for other tasks than

did writing This ought to be followed up in future researchFootedness eyedness and earedness were only investigated

with four indicators each Even though they were found toconstitute reliable and useful scales here and showed also favor-

able psychometric properties in other studies (Kalaycıoğlu et al2008 Mikheev et al 2002 Reiss 1998 Schneiders et al 2010Suar et al 2007) self-report inventories other than the LPI andlarger item banks need to be investigated in the future Further-

more even though lsquochairrsquo refers to an unskilled (balance) activityand had only low discriminatory power with regard to footednessclassi1047297cation it still 1047297tted with the skilled activities on a commonscale (cf Chapman et al (1987) Kang and Harris (2000) Mikheev

et al (2002) Schneiders et al (2010) but see Kalaycıoğlu et al(2008)) Previous analyses lacked an adequate statistical approachto take the skewedness of response distributions into accountwhich may have introduced spurious results with regard to the

assessment of dimensionality The current study did not provideany indication that self-reported handedness is multidimensional(cf Healey et al (1986) Kang and Harris 2000 Mikheev et al2002 Nicholls et al (2013) and Steenhuis and Bryden (1989))

With regard to footedness (Kalaycıoğlu et al 2008 Kang amp Harris2000 Mikheev et al 2002 Schneiders et al 2010) more researchis still needed Larger item banks need to be investigated andadequate statistical methods need to be utilized in future psycho-

metric studies to further examine the dimensionality of self-reported lateral preferences

According to our data and in contrast to footedness lsquohead-phonersquo may truly not 1047297t on a common earedness scale With the

widespread use of portable audio players in the last decadesheadphones are likely expected to be used in pairs which mayintroduce ambiguity in responding to this item Earedness is still

the least investigated of all lateral preferences more research isneeded especially with regard to its assessment

42 Self-reported lateral preferences are discrete and trichotomous

Handedness footedness eyedness and earedness as assessed

in self-report with items of the EHI and LPI were found to betaxonic and discrete containing three taxa each right mixed andleft Thus lateral preferences seem primarily a matter of differ-ences in kind ie qualitative similar across the various preference

domains but not of degree (cf Prichard Propper and Christman(2013)) Even though this does not render a dimensional con-ceptualization of lateral preferences inappropriate it highlightsthe existence of distinct categories whose differences are more

than merely dimensional This study provides prevalence esti-

mates of the three taxa in each domain and empirically derivedcutoffs that may be used in future research

Previous estimates of self-reported right-handedness (Coren1993 Peters et al 2006) and of mixed- and left-handedness(Vuoksimaa Koskenvuo Rose amp Kaprio 2009) could be broadlyreplicated in this study However it was also found that mixed

preferences need to be taken into consideration with regard to allinvestigated domains of lateral preferences Even though con1047297nedto a small minority in handedness mixed preferences were farmore frequent in footedness earedness and eyedness where in

turn right-preferences were much less frequent than previouslyreported especially in footedness (cf Bourassa et al (1996) andPorac and Coren (1976 1981)) Rates of mixed foot preferencewere however comparable to a recent study (Asai Sugimori amp

Tanno 2011) Previous studies often neglected mixed preferencesor did not differentiate mixed from left preferences The presentstudy shows that mixed preferences were relevant in all investi-gated domains and could be reliably differentiated from left and

right preferences even though mixed-handers showed somesimilarity to right-handers (see Vuoksimaa et al (2009)) Wefound no evidence however of more than three classes (eg upto eight Annett 2004) underlying self-reported handedness or

any of the other lateral preferences

43 Interrelations of lateral preferences and associationswith sex and age

Lateral preferences were concordantly interrelated across the

four domains Interrelations were strongest between handednessand footedness and weaker between and with the other lateraldomains however earedness was more strongly inter-relatedwith footedness than with handedness Considering this overall

pattern we do not consider these results to be in1047298uenced by aresponse bias in the form of a carry-over effect with participantsindiscriminately responding to other lateral preference items inthe same fashion they responded to handedness items before

(Bourassa et al 1996) Furthermore results replicated a number of previous 1047297ndings regarding (1) a higher rate of left-footedness

among men (Dittmar 2002) (2) decreasing rates of mixedpreferences among older respondents in footedness (Gabbard ampIteya 1996 Porac Coren and Duncan 1980) and eyedness(Dellatolas et al 1998 Porac et al 1980) (3) an increasing rateof left-earedness among older respondents (Porac et al 1980) In

addition we found that men were also more likely to be mixed-footed than women and that women were more likely to be left-eyed than men (also apparent but nonsigni1047297cant in the meta-analysis of Bourassa et al (1996))

44 Sidedness genetic models and cerebral dominance

Finally and most importantly this study provided converging

evidence that three classes of sidedness right mixed and left

underlay lateral preferences in self-reported handedness footednesseyedness and earedness suggesting moreover a far lower rate of

Table 11

Observed and predicted proportions derived from RS theory of combinations of left (L) and non-left (non-L) preferences (combining mixed and right preferences) for all

pairs of lateral preferences collapsing all three samples

HandndashFoot 13-rule 14-rule HandndashEye HandndashEar FootndashEye FootndashEar EyendashEar

Non-LNon-L 882 (852) (895) (885) 740 (729) 739 (738) 735 (726) 741 (734) 643 (6 41)

Non-LL 37 (68) (23) (34) 179 (191) 181 (182) 179 (188) 174 (180) 129 (129)

LNon-L 32 (32) (21) (31) 32 (41) 41 (42) 37 (44) 39 (46) 137 (139)

LL 49 (18) (61) (51) 49 (39) 40 (38) 48 (42) 46 (40) 91 (91)

χ 2 120966 28009 635 8038 219 4177 3109 60

Note χ 2frac14chi squared goodness-of-1047297t tests Predicted values are provided in parentheses To account for an observed lsquopull to concordancersquo in handndashfoot lateral preferences

the 13-rule as suggested by Annett (2000) was applied to the data (see main text) column lsquo13-rulersquo displays the respective predicted proportions As application of the 1

3-rule did not suf 1047297ciently improve model 1047297t an exploratory 14-rule was also applied to the hand ndashfoot data (column lsquo14-rulersquo)




right-sidedness in the population around 60 and a far higher rateof mixed-sidedness around 30 than would have been expectedfrom handedness rates alone Yet sidedness was less dependent onhandedness than on footedness that proved its primary indicator

Mixed- and left-sidedness were overall more frequent among mencorroborating previous 1047297ndings in children and adults (GreenwoodGreenwood McCullagh Beggs amp Murphy 2007 Suar et al 2007)and in younger participants Moreover we observed that inconsis-

tencies in preferences were more frequent in younger respondentsmixed-siders and left-siders and that crossed preferences were morefrequent among left- than right-siders This is consistent with priorevidence showing that preferences appear less lateralized among

younger respondents and that consistency in preference acrossdifferent domains increases among older respondents (Bourassa etal 1996 Dellatolas et al 1998 Dittmar 2002 Gabbard amp Iteya 1996Greenwood et al 2007 Porac 1997 Porac et al 1980 Suar et al

2007) and that crossed preferences are more frequent among left-than right-handers (Kang amp Harris 2000 see also Elias et al (1998)for an overview on studies)

The obtained evidence on a primacy of footedness appears at a

1047297rst glance suggestive of evolutionary lsquopostural controlrsquo theoriesthat consider footedness as primary to handedness with regard tocerebral lateralization (Day amp MacNeilage 1996 MacNeilage1991) Yet it appears that speci1047297cally skilled movements are

indicative of language lateralization (Elias et al 1998) instead of unskilledbalancing movements as predicted by this theory Theapparent association of footedness with earedness in our data ishowever in favor of theories positing a dependence of footedness

and of ensuing motoric lateralization on the asymmetric prenataldevelopment of the vestibular organ set in motion by the fetus rsquo in-utero position and maternal walking patterns (Previc 1991) Thereis also neuroscienti1047297c evidence linking the vestibular system with

handedness (Dieterich et al 2003)Probing predictions of single-locus genetic models our data were

consistent with RS theory (Annett 2002) but not with the DC model

(McManus 1985) Even though lateral preferences are in all likelihoodgoverned by multilocus rather than single-locus processes (McManus

et al 2013 Reiss 1999 Warren et al 2006) there is some evidencethat differences between these models statistically is only small and

may not easily be detected with classic genetic research designs(McManus et al 2013) We found that the bivariate distributions of lateral preferences could be approximated with reasonable accuracywith RS theory thus suggesting that lateral preferences may at least be

described as if they obeyed a single-locus genetic model involvingchance and an RS-allele Further RS theory appears also informativewith regard to mixed lateral preferences and mixed-sidedness alsquomiddlersquo class is implied in RS theory by genotype RSthorn It is

tempting to speculate that the relatively large class of mixed-sidersobserved in the present study in majority could possess the hypothe-tical RSthorn genotype Footedness is likely the best predictor of the RSgenotype on a behavioral level as it was the best predictor of

sidednessIn contrast self-reported handedness appears a likely biased

indicator of sidedness and speci1047297cally of mixed-sidedness In ourstudy proportions of mixed preferences in footedness eyedness

and earedness were around 14ndash35 Mixed-handedness was muchless prevalent around 2ndash3 using the 4-item short scale Withregard to this it should be noted 1047297rst that handedness is subjectto social and cultural pressures (Preti Sisti Rocchi Busca and

Vellante 2011) favoring right-handedness This affects not onlyleft-handers (McManus Moore Freegard amp Rawles 2010) butlikely also mixed-handers Second various manual tasks in handpreference inventories are performed on a regular basis in every-

day life Mixed-handers may develop a preference for one handover the other out of necessity or convenience that is reinforced

by regular practice In a mostly right-sided world (Coren amp

Halpern 1991) the preferred hand is likely the right hand againThere is also evidence of a higher accident proneness amongmixed-handers compared to right-handers (Hicks Pass FreemanBautista amp Johnson 1993) that generalizes to mixed preferences

in footedness eyedness or earedness only to a lesser extent(Mandal Sabharwal Misra Suman amp Suar 2012) Continuoususe of one hand could allow mixed-handers to adapt better to aright-sided world and could also bene1047297t their motor coordination

which may be diminished among mixed-handers (Hicks InmanDeharo amp Hicks 1999) Both effects likely diminish the accidentproneness of mixed-handers which may be another driving factorfor an lsquoacquiredrsquo hand preference among mixed-handers Third

regularity of preference of one hand over the other varied in ourdata with regard to examined tasks the proportion of mixed-handers was larger (around 7) when including tasks with anoverall higher propensity of equal hand preference for classi1047297ca-

tion like using a 1047298y 1047298apFrom this perspective self-reported handedness may be an

unreliable indicator of cerebral dominance speci1047297cally withregard to the diffuse cerebral dominance that is implied by mixed

preferences (Rodriguez amp Waldenstroumlm 2008) and the underlyingbiological and genetic processes Instead footedness may need tobe investigated more closely There is indeed evidence suggestingan association between non-right-footedness and schizophrenia

(Schiffman et al 2005) Results with regard to schizotypy andfootedness are currently inconclusive (Kelley amp Coursey 1992Nicholls Orr amp Lindell 2005) Future research may bene1047297t fromusing psychometrically validated instruments (Rodriguez et al

2010) but also from simultaneously assessing footedness besideshandedness This may help in disentangling and de1047297ning devel-opmental trajectories of neurobehavioral pathology but may alsoclarify the status of the other domains of laterality and of

sidedness as a risk factorEven though consistent with our data our results suggest that RS

theory needs to be supplemented with further genetic prenatal

developmental and environmental factors in order to arrive at a validoverall model of lateral preferences First inconsistent and crossed

preferences were frequently observed in our data in handndashear andhandndasheye pairings requiring the modeling of residual interdependen-

cies of handedness and footedness and of eyedness and earednessover and above sidedness In terms of RS theory there was a lsquopull toconcordancersquo in handndashfoot preferences which may stem from sharedsensori-motor control systems (Annett 2000 Annett 2002) This is

direct evidence of a complex interrelationship of lateral preferencesoverall Second self-reported lateral preferences were subject to sexand age effects being suggestive of further genetic prenatal anddevelopmental in1047298uences (Annett 2004) However whatever the

de1047297nitive overall model of lateral preferences it appears likely thatfootedness not handedness plays a prominent role in it given theevidence accumulated here We recommend the use of a trichotomy(right vs mixed vs left) for the classi1047297cation of lateral preferences in

future studies which may speci1047297cally bene1047297t genetic studies Thepresent line of research should also be followed up using family andtwin study designs in order to examine predictions and the validity of RS theory further

5 Limitations

Limitations of our study pertain to the utilized measures of lateral preferences We examined only self-reported lateral pre-ferences using items of only two speci1047297c but widely-usedinventories Results may thus not generalize to inventories other

than the EHI and the LPI or to measures of ability or performanceMoreover participants were not asked to actually perform the

tasks This may have prompted higher numbers of lsquono preferencersquo




responses (see Byrne et al (2004)) which may have impacted onresults

6 Conclusions

This study provided converging evidence on the taxonity of self-reported handedness footedness eyedness and earedness

highlighting that it is primarily qualitative differences that differ-entiate these lateral preferences Across domains lateral prefer-ences were overall concordant Three classes of sidedness werefound to underlie but could not fully explain the interrelations of

lateral preferences The observed interrelations were further con-sistent with predictions of right shift theory In combination with anumber of additional 1047297ndings regarding associations of lateralpreferences with sex and age results were in sum suggestive of a

complex and multifactorial model of lateral preferences Theprimacy of footedness with regard to overall sidedness needs tobe investigated in more detail in future research More generallylaterality research may bene1047297t from using psychometricallyvalidated self-report measures and utilizing a trichotomy in

classi1047297cation

Acknowledgments

Thanks are extended to Ingrid Koller Ingo W Nader JakobPietschnig Anne H E Schild and Elisabeth L Zeilinger forsupporting the data collection with regard to the two comparisonsamples analyzed in this study

Appendix A Supporting information

Supplementary data associated with this article can be found inthe online version at httpdxdoiorg101016jneuropsychologia

201407027

References

Annett M (2000) Predicting combinations of left and right asymmetries Cortex 36 485ndash505

Annett M Handedness and brain asymmetry the right shift theory 2002Psychology Press Hove UK

Annett M (2004) Hand preference observed in large healthy samples classi1047297ca-tion norms and interpretations of increased non-right-handedness by the rightshift theory British Journal of Psychology 95 339ndash353

Asai T Sugimori E amp Tanno Y (2011) A psychometric approach to the relation-ship between handndashfoot preference and auditory hallucinations in the generalpopulation atypical cerebral lateralization may cause an abnormal sense of agency Psychiatry Research 189 220ndash227

Asendorpf J B Conner M De Fruyt F De Houwer J Denissen J J Fiedler Ket al (2013) Recommendations for increasing replicability in psychologyEuropean Journal of Personality 27 108ndash119

Beaton A A (2008) Handedness assessment in studies of seasonal anisotropyCortex 44 97ndash98Beauducel A amp Herzberg P Y (2006) On the performance of maximum likelihood

versus means and variance adjusted weighted least squares estimation in CFAStructural Equation Modeling 13 186ndash203

Bernstein I H amp Teng G (1989) Factoring items and factoring scales are differentspurious evidence for multidimensionality due to item categorization Psycho-logical Bulletin 105 467ndash477

Bourassa D C McManus I C amp Bryden M P (1996) Handedness and eye-dominance a meta-analysis of their relationship Laterality 1 5ndash34

Byrne M Clafferty R A Cosway R Grant E Hodges A Lawrie S M et al(2004) Measurement of lateral preferences and schizophrenia results of theEdinburgh high-risk study and methodological issues Psychiatry Research 125205ndash217

Carey D P Smith D T Martin D Smith G Skriver J Rutland A et al (2009)The bi-pedal ape plasticity and asymmetry in footedness Cortex 45 650ndash661

Chapman J P Chapman L J amp Allen J J (1987) The measurement of footpreference Neuropsychologia 25 579ndash584

Collins L M amp Lanza S T (2010) Latent class and latent transition analysis for the

social behavioral and health sciences New York Wiley

Corballis M C amp Morgan M J (1978) On the biological basis of human laterality IEvidence for a maturational leftndashright gradient Behavioural and Brain Sciences

2 261ndash269Coren S (1993) The left-hander syndrome the causes and consequences of left-

handedness New York Vintage BooksCoren S amp Halpern D F (1991) Left-handedness a marker for decreased survival

1047297tness Psychological Bulletin 109 90ndash106Crow T J (2013) The XY gene hypothesis of psychosis origins and current status

American Journal of Medical Genetics B 162 800ndash824Day L B amp MacNeilage P H (1996) Postural asymmetries and language

lateralisation in humans (Homo sapiens) Journal of Comparative Psychology110 88ndash96

Dellatolas G Curt F Dargent-Pareacute C amp De Agostini M (1998) Eye dominance inchildren a longitudinal study Behavior Genetics 28 187ndash195

Dieterich M Bense S Lutz S Drzezga A Stephan T Bartenstein P et al (2003)Dominance for vestibular cortical function in the non-dominant hemisphereCerebral Cortex 13 994ndash1007

Dittmar M (2002) Functional and postural lateral preferences in humansinterrelations and life-span age differences Human Biology 74 569ndash585

Dragovic M (2004) Towards an improved measure of the Edinburgh handednessinventory a one-factor congeneric measurement model using con1047297rmatoryfactor analysis Laterality 9 411ndash419

Dragovic M amp Hammond G (2005) Handedness in schizophrenia a quantitativereview of evidence Acta Psychiatrica Scandinavica 111 410ndash419

Dragovic M amp Hammond G (2007) A classi1047297cation of handedness using theAnnett Hand Preference Questionnaire British Journal of Psychology 98375ndash387

Dragovic M Milenkovic S amp Hammond G (2008) The distribution of handpreference is discrete a taxometric examination British Journal of Psychology

99 445ndash459Elias L J amp Bryden M P (1998) Footedness is a better predictor of language

lateralisation than handedness Laterality 3 41ndash51Elias L J Bryden M P amp Bulman-Fleming M B (1998) Footedness is a better

predictor than is handedness of emotional lateralization Neuropsychologia 36 37ndash43

Gabbard C amp Iteya M (1996) Foot laterality in children adolescents and adultsLaterality 1 199ndash205

Golembo-Smith S Schiffman J Kline E Soslashrensen H J Mortensen E LStapleton L et al (2012) Premorbid multivariate markers of neurodevelop-mental instability in the prediction of adult schizophrenia-spectrum disorder ahigh-risk prospective investigation Schizophrenia Research 139 129ndash135

Greenwood J G Greenwood J J D McCullagh J F Beggs J amp Murphy C A(2007) A survey of sidedness in Northern Irish schoolchildren the interactionof sex age and task Laterality 12 1ndash18

Haslam N Holland E amp Kuppens P (2012) Categories versus dimensions inpersonality and psychopathology a quantitative review of taxometric researchPsychological Medicine 42 903ndash920

Healey J M Liederman J amp Geschwind N (1986) Handedness is not aunidimensional trait Cortex 22 33ndash53Hicks R A Inman G Deharo D amp Hicks G J (1999) Consistency of hand use and

frequent falls Perceptual and Motor Skills 88 1107ndash1110Hicks R A Pass K Freeman H Bautista J amp Johnson C (1993) Handedness and

accidents with injury Perceptual and Motor Skills 77 1119ndash1122Hu L T amp Bentler P M (1999) Cutoff criteria for 1047297t indexes in covariance structure

analysis conventional criteria versus new alternatives Structural Equation

Modeling 6 1ndash55Kalaycıoğlu C Kara C Atbaşoğlu C amp Nalccedilacı E (2008) Aspects of foot

preference differential relationships of skilled and unskilled foot movementswith motor asymmetry Laterality 13 124ndash142

Kang Y amp Harris L J (2000) Handedness and footedness in Koreancollege students Brain and Cognition 43 268ndash274

Kelley M P (2012) Lateral preference and schizotypy revisited comparison of handedness measurement and classi1047297cation methods Laterality 17 150ndash168

Kelley M P amp Coursey R D (1992) Lateral preference and neuropsychologicalcorrelates of schizotypy Psychiatry Research 41 115ndash135

Kenny D A Kaniskan B amp McCoach D B (2014) The performance of RMSEA in

models with small degrees of freedom Sociological Methods amp ResearchAdvance online publication httpdxdoiorg1011770049124114543236

MacNeilage P F (1991) The ldquopostural originsrdquo theory of primate neurobiologicalsymmetries In N A Krasnegor D M Rumbaugh R L Schiefelbusch ampM Studdert-Kennedy (Eds) Biological and behavioural determinants of language

development (pp 165ndash188) Hillsdale NJ ErlbaumMandal M K Sabharwal A Misra I Suman S amp Suar D (2012) Mixed-sided

individuals with neuroticism sustain more unintentional injuries in IndiaInternational Journal of Psychology 47 296ndash304

McCarthy M I Abecasis G R Cardon L R Goldstein D B Little J Ioannidis J PA et al (2008) Genome-wide association studies for complex traits con-sensus uncertainty and challenges Nature Reviews Genetics 9 356ndash369

McManus I C (1985) Handedness language dominance and aphasia A geneticmodel Psychological Medicine Monograph Suppl 8 Cambridge CambridgeUniversity Press

McManus I C Davison A amp Armour A L (2013) Multilocus genetic models of handedness closely resemble single-locus models in explaining family data andare compatible with genome-wide association studies Annals of the New York

Academy of Sciences 1288 48ndash58




McManus I C Moore J Freegard M amp Rawles R (2010) Science in the makingright hand left hand III estimating historical rates of left-handednessLaterality 15 186ndash208

McManus I C Porac C Bryden M P amp Boucher R (1999) Eye-dominancewriting hand and throwing hand Laterality 4 173ndash192

Meehl P E (2004) Whats in a taxon Journal of Abnormal Psychology 113 39ndash43Meehl P E amp Yonce L J (1994) Taxometric analysis I Detecting taxonicity with

two quantitative indicators using means above and below a sliding cut(MAMBAC procedure) Psychological Reports 74 1059ndash1274

Merni F Di Michele R amp Soffritti G (2013) Assessment of handedness usinglatent class factor analysis Laterality 19 405ndash423

Mikheev M Mohr C Afanasiev S Landis T amp Thut G (2002) Motor control andcerebral hemispheric specialization in highly quali1047297ed judo wrestlers Neurop-sychologia 40 1209ndash1219

Milenkovic S amp Dragovic M (2013) Modi1047297cation of the Edinburgh handednessinventory a replication study Laterality 18 340ndash348

Mutheacuten L K amp Mutheacuten B O (2008) Mplus user rsquo s guide Los Angeles CA Mutheacuten ampMutheacuten

Nicholls M E Orr C A amp Lindell A K (2005) Magical ideation and its relation tolateral preference Laterality 10 503ndash515

Nicholls M E R Thomas N A Loetscher T amp Grimshaw G M (2013) TheFlinders Handedness survey (FLANDERS) a brief measure of skilled handpreference Cortex 49 2914ndash2926

Noonan M amp Axelrod S (1981) Earedness (ear choice in monaural tasks) itsmeasurement and relationship to other lateral preferences Journal of AuditoryResearch 21 263ndash277

Old1047297eld R C (1971) The assessment and analysis of handedness the Edinburghinventory Neuropsychologia 9 97ndash113

Papadatou-Pastou M Martin M Munafogravem M R amp Jones G V (2008) Sex

differences in left-handedness a meta-analysis of 144 studies PsychologicalBulletin 134 677ndash699Peters M Reimers S amp Manning J T (2006) Hand preference for writing and

associations with selected demographic and behavioral variables in 255100subjects the BBC Internet study Brain and Cognition 62 177ndash189

Porac C (1997) Eye preference patterns among left-handed adults Laterality 2 305ndash316

Porac C amp Coren S (1976) The dominant eye Psychological Bulletin 83880ndash897

Porac C amp Coren S (1981) Lateral preferences and human behavior New YorkSpringer

Porac C Coren S amp Duncan P (1980) Life-span age trends in laterality Journal of Gerontology 35 715ndash721

Preti A Sisti D Rocchi M B Busca M amp Vellante M (2011) Male-femaledifferences in left-handedness in Sardinia Italy Laterality 16 737ndash752

Previc F H (1991) A general theory concerning the prenatal origins of cerebrallateralisation in humans Psychological Review 98 299ndash334

Prichard E Propper R E amp Christman S D (2013) Degree of handedness but notdirection is a systematic predictor of cognitive performance Frontiers

in Psychology 4 9 httpdxdoiorg103389fpsyg201300009Reiss M (1998) Current investigations of earedness Folia Phoniatrica et Logopae-

dica 50 19ndash27Reiss M (1999) Genetic associations between lateral signs Anthropologischer

Anzeiger 57 61ndash68Reiss M Tymnik G Koumlgler P Koumlgler W amp Reiss G (1999) Laterality of hand

foot eye and ear in twins Laterality 4 287ndash297Reiss M amp Reiss G (1999) Earedness and handedness distribution in a German

sample with some family data Cortex 35 403ndash412Rodriguez A Kaakinen M Moilanen I Taanila A McGough J J Loo S et al

(2010) Mixed-handedness is linked to mental health problems in childrenand adolescents Pediatrics 125 e340

Rodriguez A amp Waldenstroumlm U (2008) Fetal origins of child non-right-handednessand mental health Journal of Child Psychology and Psychiatry 49 967ndash976

Ruscio J (2012) Taxometric Programs for the R Computing Environment User rsquo s

Manual [computer software and manual] langhttpwwwtcnjedurusciotaxometricshtmlrang (Retrieved from 280613)

Ruscio J amp Kaczetow W (2009) Differentiating categories and dimensionsevaluating the robustness of taxometric analyses Multivariate Behavioral

Research 44 259ndash280Ruscio J Walters G D Marcus D K amp Kaczetow W (2010) Comparing the

relative 1047297t of categorical and dimensional latent variable models using

consistency tests Psychological Assessment 22 5ndash

21Sadeghi H Allard P Prince F amp Labelle H (2000) Symmetry and limbdominance in able-bodied gait a review Gait Posture 12 34ndash45

Samejima F (1969) Estimation of latent ability using a response pattern of gradedscores Psychometric Monograph No 17 Richmond VA Psychometric Society

Schiffman J Pestle S Mednick S Ekstrom M Sorensen H amp Mednick S (2005)Childhood laterality and adult schizophrenia spectrum disorders a prospectiveinvestigation Schizophrenia Research 72 151ndash160

Schneiders A G Sullivan J OrsquoMalley K J Clarke S V Knappstein S A amp TaylorL J (2010) A valid and reliable clinical determination of footedness Physical

Medicine and Rehabilitation 2 835ndash841Searleman A (1980) Subject variables and cerebral organization for language

Cortex 16 239ndash254Somers M Sommer I Boks M amp Kahn R (2009) Hand preference and

population schizotypy a meta-analysis Schizophrenia Research 108 25ndash32Sommer I Ramsey N Kahn S Aleman A amp Bouma A (2001) Handedness

language lateralisation and anatomical asymmetry in schizophrenia meta-analysis British Journal of Psychiatry 178 344ndash351

Steenhuis R E amp Bryden M P (1989) Different dimensions of hand preferencethat relate to skilled and unskilled activities Cortex 25 289ndash304Strauss E (1986) Hand foot eye and ear preferences and performance on a

dichotic listening test Cortex 22 475ndash482Suar D Mandal M K Misra I amp Suman S (2007) Lifespan trends of side bias in

India Laterality 12 302ndash320Sza1047298arski J P Binder J R Possing E T McKiernan K A Ward B D amp Hammeke

T A (2002) Language lateralization in left-handed and ambidextrous peoplefMRI data Neurology 59 238ndash244

Sza1047298arski J P Holland S K Schmithorst V J amp Byars A W (2006) fMRI study of language lateralization in children and adults Human Brain Mapping 27 202ndash212

Veale J F (2013) Edinburgh handedness inventoryndashshort form a revised versionbased on con1047297rmatory factor analysis Laterality 19 164ndash177 httpdxdoiorg1010801357650X2013783045

Vuoksimaa E Koskenvuo M Rose R J amp Kaprio J (2009) Origins of handednessa nationwide study of 30161 adults Neuropsychologia 47 1294ndash1301

Waller N G amp Meehl P E (1998) Multivariate taxometric procedures distinguishing

types from continua Thousand Oaks CA SageWarren D M Stern M Duggirala R Dyer T D amp Almasy L (2006) Heritability

and linkage analysis of hand foot and eye preference in Mexican AmericansLaterality 11 508ndash524

Willems R M Van der Haegen L Fisher S E amp Francks C (2014) On the otherhand including left-handers in cognitive neuroscience and neurogeneticsNature Reviews Neuroscience 15 193ndash201




of the lateral preferences that are of concern here (Porac amp Coren1981) Similarly to eyedness sensory dominance or differences inacuity in binaural activities need to be conceptually distinguishedfrom earedness (Noonan amp Axelrod 1981) Earedness is only

weakly functional asymmetric about 60 of the population beingright-eared (Porac amp Coren 1981) but is apparently a betterpredictor of language lateralization than handedness footednessor eyedness (Strauss 1986)

A plethora of studies has provided evidence that overall lateralpreferences in handedness footedness eyedness and earednessare concordantly interrelated with associations between handed-ness and footedness being often strongest (Bourassa et al 1996

Dellatolas Curt Dargent-Pareacute amp De Agostini 1998 Dittmar 2002Kang amp Harris 2000 McManus Porac Bryden amp Boucher 1999Noonan amp Axelrod 1981 Porac 1997 Reiss 1999 Reiss amp Reiss1999 Suar Mandal Misra amp Suman 2007) Thus lateral prefer-

ences may share a common genetic or biological origin primary oroverall sidedness (Annett 2002 Corballis amp Morgan 1978McManus 1985 Previc 1991) While family and genetic studiessuggest (strong) familial aggregations and (weak) genetic associa-

tions (Bourassa et al 1996 Dellatolas et al 1998 McManus et al1999 Reiss 1999 Reiss amp Reiss 1999 Warren Stern DuggiralaDyer amp Almasy 2006) some twin studies have failed to con1047297rmthe genetic determination of sidedness (Reiss Tymnik Koumlgler

Koumlgler amp Reiss 1999) To date a complex multigenetic and multi-factorial model of lateral preferences and their interrelationsappears most likely (McManus Davison amp Armour 2013 Reiss1999 Warren et al 2006)

However research into lateral preferences faces some impor-tant methodological problems First given the skewed distribu-tions of lateral preferences sample size and study power are anissue For example the 1090 handedness ratio lowers the power

of statistical tests by about 50 compared to a 5050 ratio Largesamples are thus required

Second classi1047297cation of lateral preferences frequently adopts either

a dichotomy (rightleft and rightnon-right) or a trichotomy (rightmixedleft) often based on arbitrary criteria and cutoffs on dimen-

sional continuous measures This heterogeneity may prohibit directcomparisons between studies (Beaton 2008) and may also lead to

vastly different results even with the same data (Kelley 2012) Most of the above reviewed studies used dichotomies for classi1047297cation (but seeDittmar (2002) Gabbard and Iteya (1996) and Kang and Harris(2000)) However there is evidence from latent variable analyses that

at least for handedness a trichotomy may be more adequate (Dragovicamp Hammond 2007 Dragovic Milenkovic amp Hammond 2008)

Third with regard to assessment itself the use of multi-iteminventories is recommended The use of single items (such as lsquowriting

handrsquo for handedness) may entail the underestimation of interrela-tions of lateral preferences (Bourassa et al 1996 McManus et al 1999Warren et al 2006) and of associations with other variables such assex (Papadatou-Pastou Martin Munafogravem amp Jones 2008) Yet

existing multi-item inventories like the Edinburgh HandednessInventory (EHI Old1047297eld 1971) and the Lateral Preference Inventory(LPI Coren1993) differ with regard to item composition and responseformat and rigorous psychometric analyses are scarce Existing ana-lyses suggest that some items of widely-used self-report inven-

tories are inappropriate for the accurate assessment of handedness(Dragovic 2004 Dragovic amp Hammond 2007 Milenkovic amp Dragovic2013 Veale 2013) and that skilled and unskilled activities may

constitute separate factors in handedness (Healey Liederman ampGeschwind 1986 Kang amp Harris 2000 Mikheev Mohr AfanasievLandis amp Thut 2002 Nicholls Thomas Loetscher amp Grimshaw2013 Steenhuis amp Bryden 1989) and footedness (Kalaycıoğlu Kara

Atbaşoğlu and Nalccedilacı 2008 Kang amp Harris 2000 Mikheev et al2002 Schneiders et al 2010) However the reported multidimension-

ality of handedness and footedness may have been spurious Studies

relied on factor-analytic methods that were not suited for the highlyskewed item response distributions that are typically encountered inlateral preference inventories This may have resulted in an over-extraction of factors (see Bernstein and Teng (1989)) caused by the

clustering of items with similar distributional properties in differentfactors With regard to response format it is unclear whether threecategories delineating lsquorightrsquo lsquoleftrsquo and lsquono preferencersquo as in the LPI or

1047297ve categories differentiating within lsquoleftrsquo and lsquorightrsquo between lsquoalwaysrsquo

and lsquousually

rsquo as in revised versions of the EHI (Veale 2013) are bettersuited for the assessment of lateral preferences

Overall there is a dearth of psychometric and latent variableanalyses with regard to the assessment and classi1047297cation of self-

reported lateral preferences even though such analyses are of importance for the various and numerous 1047297elds of applied lateralityresearch

Recent studies point out that mixed-handedness may be a risk

factor for neurodevelopmental and neurobehavioral disorders(eg ADHD and language problems Rodriguez et al 2010 schizo-phrenia Dragovic amp Hammond 2005 Sommer Ramsey KahnAleman amp Bouma 2001 schizotypy Somers Sommer Boks amp

Kahn 2009) as mixed-handedness is considered an observablemanifestation of underlying neurodevelopmental instability(Golembo-Smith et al 2012 Rodriguez amp Waldenstroumlm 2008)and de1047297cits in lateralization (Crow 2013) Recently Willems Van

der Haegen Fisher and Francks (2014) have advocated speci1047297callyincluding left-handers in neuroscienti1047297c and neurogenetic studiesinstead of excluding them this would further know-ledge of brain functioning and allow a deeper insight into cerebral

lateralization and its genetic underpinnings as it is currently thecase However there is a need for psychometrically validatedinstruments that can be reliably used in applied research(Rodriguez et al 2010)

The present study addressed the above issues By design ourstudy comprised three independent large samples (total

N 415100) following recent recommendations to counteract

potentially false-positive and thus irreproducible research 1047297nd-ings (Asendorpf et al 2013) In genome-wide association stu-

dies independent discovery and replication samples within thesame study are considered best practice in order to guard

against false-positive 1047297ndings and to demonstrate the robust-ness of an effect if the replication is successful ( McCarthy et al2008) The present study included one sample (n42400) inwhich self-reported handedness was assessed with more items

than in the other two samples (total n412700) This sampleserved for calibration purposes (calibration sample) whereasthe other two samples served for the purpose of cross-validation (comparison sample 1 and 2) With regard to all

other lateral preferences the three samples were full replicationsamples of each other

First we investigated the dimensional structure item proper-ties and optimal number of response categories of widely-used

self-report measures of lateral preferences in handedness footed-ness eyedness and earedness with structural equation modeling(SEM) and item response theory (IRT) Second using two inde-pendent approaches latent class analysis and taxometric analysis

we determined whether lateral preferences were categorical ordimensional providing empirically derived cutoffs that may beused in future research Third interrelations between lateralpreferences were examined investigating evidence for underlying

overall sidedness and also investigating the in1047298uence of sex andage on lateral preferences and sidedness Fourth the observedpairwise associations of lateral preferences were utilized to probepredictions of two speci1047297c single-locus genetic models right shift(RS) theory (Annett 2000 Annett 2002) and the dextral and

chance allele model (DC model McManus 1985) (for background

and details see Section 236 below)





21 Participants



























































































comparison samples




















also reported

Table 1


Sample


n 2455 7658 5062

Women n () 1240 (507)a 4456 (582) 2749 (543)



Nationality n ()c

Austria 1397 (573) 5339 (700) 3415 (677)

Germany 923 (378) 1773 (232) 1310 (260)

Other 119 (49) 514 (67) 316 (63)































100














235 Sidedness





























3 Results


















right








































Table 2




16 items 85215 (104) 994 993 054 [051058]

10 items 28141 (35) 998 997 054 [048059]






Footedness 473 (2) 999 998 024 [000052]

Eyedness 1949 (2) 1000 999 060 [037085]

Earedness 7331 (2) 994 982 121 [098145]



Table 3




Writing 95 94 96 95

Drawing 96


Tennis 94 94 98

Toothbrush 91 91 96

Knife 92 92 96 97

Hammer 98 98 99 99n

Match 88


Needle 69

Fly 1047298ap 93 93 97

Scissors 92 92 97

Spoon 91 91 95

Broom 68

Box 78













































37 Sidedness




Table 4




3-cluster 486644 62 1021682 178731 2394 1000 164

4-cluster 476613 83 1018012 158667 2371 1000 191

5-cluster 471353 104 1023883 148146 2350 1000 240


boldface









Table 5




Class size 849 071 079900n 021n 078n 895 028 077 890 026 084

CCFI 66 76

59n 76n 67 87 88 63LQ cutoffs 472 72 to 7 o7

441n 41 to 40n o40n 441 41 to 40 o40 441 41 to 40 o40

Writing 0 00 099 170281 720028

010099n 330660n 720028n 010099 132166 80 0119 010099 242056 740225

Thr owing 00 0099 131473 890209

010199n 223741n 920108n 010298 095536 83 0413 010198 145036 870311

Tennis 000199 121770 910504


010198n 362538n 900010n 010197 136225 83 0313 010198 124841 830413Hammer 0 00 099 091180 970103

000099n 303733n 970003n 000199 095933 91 0306 000199 095833 920206

Eraser 000298 204139 880408

Fly 1047298ap 000297 054747 851103

Scissors 0 00 099 082072 830215

Spoon 000298 172359 830511





Table 6




Footedness

Class size 632 261 106 566 347 086 595 314 091

CCFI 76 87 78 85 77 76


Ball (8460) 010298 051976 680923 010297 042769 651323 010297 052669 700822

Pebble (8466) 011089 027227 711811 030592 027027 731908 030592 046730 781309

Be etle ( 83 66) 01 0891 007228 553015 031186 017921 533116 021187 018019 572816Chair (67 51) 08 0884 105139 691516 110980 095537 711515 110782 095437 721315

Eyedness

Class size 630 141 229 567 211 220 572 201 227

CCFI 79 81 72 89 76 84


Bo ttle (95 82) 01 0693 048313 86 0806 020692 038413 86 0707 020692 048412 831007

Keyhole (9684) 010495 048016 88 0606 020692 047719 85 0708 020494 047719 870607

Gun (9070) 030394 113356 800614 030295 094050 760618 030295 113851 770519

Earedness

Class size 517 286 197 471 315 214 498 286 216

CCFI 79 85 82 85 85 79


Heartbeat (90n 76) 030989 048115 83 0909 050986 048214 801010 040888 058213 830809

Clock (90n81) 030394 087418 92 0206 030592 068014 89 0506 030493 077914 880606




























(ORfrac14243 [215 275] po001)













143 [136ndash151])

4 Discussion


Table 7


Variable Mixed Left

Sex (male) 90 [60 133] 136 [106 174]na

Age 100 [99 101] 100 [100 101]




Left-eyed 212 [156 289]nnn 448 [377 532]nnn

Mixed-eared 140 [107 184]n 133 [110 161]nn

Left-eared 126 [90 175] 174 [145 209]nnn









41 Assessment








Table 9



1-cluster 4933925 8 9875552 860201 72 o 001 00

2-cluster 4687699 17 9391764 367749 63 o 001 846

3-cluster 4537554 26 9100139 67459 54 o 001 1304



4-cluster 4520011 35 9073717 32372 45 o 001 2174


boldface

Table 10





Handedness 010098 050589 620533 033067 087319 682012

Footedness 010099 009406 890605 010397 009802 910009

Eyedness 201268 183546 591525 042472 075538 232453

Earedness 18 1963 155233 532423 042076 075340 232354


classes

Table 8







285]nnn137 [104 181]n 127 [91 177]

Left-handed 304 [250 370]nnn 4308 [3560

5213]nnn187 [151 231]nnn 449 [378

533]nnn140 [116 169]nnn 175 [146 211]nnn


122 [110 135]nnn

365 [334 398]nnn

156 [140 174]nnn

Left-footed 181 [147 225]nnn 244 [207

289]nnn201 [166 243]nnn 349 [293

415]nnn



284]nnn



284]nnn


R2

537332 (22) po 001

363

323077 (22) po 001

224

328511 (20) po 001

224










































Table 11




Non-LNon-L 882 (852) (895) (885) 740 (729) 739 (738) 735 (726) 741 (734) 643 (6 41)

Non-LL 37 (68) (23) (34) 179 (191) 181 (182) 179 (188) 174 (180) 129 (129)

LNon-L 32 (32) (21) (31) 32 (41) 41 (42) 37 (44) 39 (46) 137 (139)

LL 49 (18) (61) (51) 49 (39) 40 (38) 48 (42) 46 (40) 91 (91)

χ 2 120966 28009 635 8038 219 4177 3109 60














































5 Limitations








6 Conclusions





classi1047297cation

Acknowledgments




201407027

References


















































































































21 Participants



























































































comparison samples




















also reported

Table 1


Sample


n 2455 7658 5062

Women n () 1240 (507)a 4456 (582) 2749 (543)



Nationality n ()c

Austria 1397 (573) 5339 (700) 3415 (677)

Germany 923 (378) 1773 (232) 1310 (260)

Other 119 (49) 514 (67) 316 (63)































100














235 Sidedness





























3 Results


















right








































Table 2




16 items 85215 (104) 994 993 054 [051058]

10 items 28141 (35) 998 997 054 [048059]






Footedness 473 (2) 999 998 024 [000052]

Eyedness 1949 (2) 1000 999 060 [037085]

Earedness 7331 (2) 994 982 121 [098145]



Table 3




Writing 95 94 96 95

Drawing 96


Tennis 94 94 98

Toothbrush 91 91 96

Knife 92 92 96 97

Hammer 98 98 99 99n

Match 88


Needle 69

Fly 1047298ap 93 93 97

Scissors 92 92 97

Spoon 91 91 95

Broom 68

Box 78













































37 Sidedness




Table 4




3-cluster 486644 62 1021682 178731 2394 1000 164

4-cluster 476613 83 1018012 158667 2371 1000 191

5-cluster 471353 104 1023883 148146 2350 1000 240


boldface









Table 5




Class size 849 071 079900n 021n 078n 895 028 077 890 026 084

CCFI 66 76

59n 76n 67 87 88 63LQ cutoffs 472 72 to 7 o7

441n 41 to 40n o40n 441 41 to 40 o40 441 41 to 40 o40

Writing 0 00 099 170281 720028

010099n 330660n 720028n 010099 132166 80 0119 010099 242056 740225

Thr owing 00 0099 131473 890209

010199n 223741n 920108n 010298 095536 83 0413 010198 145036 870311

Tennis 000199 121770 910504


010198n 362538n 900010n 010197 136225 83 0313 010198 124841 830413Hammer 0 00 099 091180 970103

000099n 303733n 970003n 000199 095933 91 0306 000199 095833 920206

Eraser 000298 204139 880408

Fly 1047298ap 000297 054747 851103

Scissors 0 00 099 082072 830215

Spoon 000298 172359 830511





Table 6




Footedness

Class size 632 261 106 566 347 086 595 314 091

CCFI 76 87 78 85 77 76


Ball (8460) 010298 051976 680923 010297 042769 651323 010297 052669 700822

Pebble (8466) 011089 027227 711811 030592 027027 731908 030592 046730 781309

Be etle ( 83 66) 01 0891 007228 553015 031186 017921 533116 021187 018019 572816Chair (67 51) 08 0884 105139 691516 110980 095537 711515 110782 095437 721315

Eyedness

Class size 630 141 229 567 211 220 572 201 227

CCFI 79 81 72 89 76 84


Bo ttle (95 82) 01 0693 048313 86 0806 020692 038413 86 0707 020692 048412 831007

Keyhole (9684) 010495 048016 88 0606 020692 047719 85 0708 020494 047719 870607

Gun (9070) 030394 113356 800614 030295 094050 760618 030295 113851 770519

Earedness

Class size 517 286 197 471 315 214 498 286 216

CCFI 79 85 82 85 85 79


Heartbeat (90n 76) 030989 048115 83 0909 050986 048214 801010 040888 058213 830809

Clock (90n81) 030394 087418 92 0206 030592 068014 89 0506 030493 077914 880606




























(ORfrac14243 [215 275] po001)













143 [136ndash151])

4 Discussion


Table 7


Variable Mixed Left

Sex (male) 90 [60 133] 136 [106 174]na

Age 100 [99 101] 100 [100 101]




Left-eyed 212 [156 289]nnn 448 [377 532]nnn

Mixed-eared 140 [107 184]n 133 [110 161]nn

Left-eared 126 [90 175] 174 [145 209]nnn









41 Assessment








Table 9



1-cluster 4933925 8 9875552 860201 72 o 001 00

2-cluster 4687699 17 9391764 367749 63 o 001 846

3-cluster 4537554 26 9100139 67459 54 o 001 1304



4-cluster 4520011 35 9073717 32372 45 o 001 2174


boldface

Table 10





Handedness 010098 050589 620533 033067 087319 682012

Footedness 010099 009406 890605 010397 009802 910009

Eyedness 201268 183546 591525 042472 075538 232453

Earedness 18 1963 155233 532423 042076 075340 232354


classes

Table 8







285]nnn137 [104 181]n 127 [91 177]

Left-handed 304 [250 370]nnn 4308 [3560

5213]nnn187 [151 231]nnn 449 [378

533]nnn140 [116 169]nnn 175 [146 211]nnn


122 [110 135]nnn

365 [334 398]nnn

156 [140 174]nnn

Left-footed 181 [147 225]nnn 244 [207

289]nnn201 [166 243]nnn 349 [293

415]nnn



284]nnn



284]nnn


R2

537332 (22) po 001

363

323077 (22) po 001

224

328511 (20) po 001

224










































Table 11




Non-LNon-L 882 (852) (895) (885) 740 (729) 739 (738) 735 (726) 741 (734) 643 (6 41)

Non-LL 37 (68) (23) (34) 179 (191) 181 (182) 179 (188) 174 (180) 129 (129)

LNon-L 32 (32) (21) (31) 32 (41) 41 (42) 37 (44) 39 (46) 137 (139)

LL 49 (18) (61) (51) 49 (39) 40 (38) 48 (42) 46 (40) 91 (91)

χ 2 120966 28009 635 8038 219 4177 3109 60














































5 Limitations








6 Conclusions





classi1047297cation

Acknowledgments




201407027

References










































































































































100














235 Sidedness





























3 Results


















right








































Table 2




16 items 85215 (104) 994 993 054 [051058]

10 items 28141 (35) 998 997 054 [048059]






Footedness 473 (2) 999 998 024 [000052]

Eyedness 1949 (2) 1000 999 060 [037085]

Earedness 7331 (2) 994 982 121 [098145]



Table 3




Writing 95 94 96 95

Drawing 96


Tennis 94 94 98

Toothbrush 91 91 96

Knife 92 92 96 97

Hammer 98 98 99 99n

Match 88


Needle 69

Fly 1047298ap 93 93 97

Scissors 92 92 97

Spoon 91 91 95

Broom 68

Box 78













































37 Sidedness




Table 4




3-cluster 486644 62 1021682 178731 2394 1000 164

4-cluster 476613 83 1018012 158667 2371 1000 191

5-cluster 471353 104 1023883 148146 2350 1000 240


boldface









Table 5




Class size 849 071 079900n 021n 078n 895 028 077 890 026 084

CCFI 66 76

59n 76n 67 87 88 63LQ cutoffs 472 72 to 7 o7

441n 41 to 40n o40n 441 41 to 40 o40 441 41 to 40 o40

Writing 0 00 099 170281 720028

010099n 330660n 720028n 010099 132166 80 0119 010099 242056 740225

Thr owing 00 0099 131473 890209

010199n 223741n 920108n 010298 095536 83 0413 010198 145036 870311

Tennis 000199 121770 910504


010198n 362538n 900010n 010197 136225 83 0313 010198 124841 830413Hammer 0 00 099 091180 970103

000099n 303733n 970003n 000199 095933 91 0306 000199 095833 920206

Eraser 000298 204139 880408

Fly 1047298ap 000297 054747 851103

Scissors 0 00 099 082072 830215

Spoon 000298 172359 830511





Table 6




Footedness

Class size 632 261 106 566 347 086 595 314 091

CCFI 76 87 78 85 77 76


Ball (8460) 010298 051976 680923 010297 042769 651323 010297 052669 700822

Pebble (8466) 011089 027227 711811 030592 027027 731908 030592 046730 781309

Be etle ( 83 66) 01 0891 007228 553015 031186 017921 533116 021187 018019 572816Chair (67 51) 08 0884 105139 691516 110980 095537 711515 110782 095437 721315

Eyedness

Class size 630 141 229 567 211 220 572 201 227

CCFI 79 81 72 89 76 84


Bo ttle (95 82) 01 0693 048313 86 0806 020692 038413 86 0707 020692 048412 831007

Keyhole (9684) 010495 048016 88 0606 020692 047719 85 0708 020494 047719 870607

Gun (9070) 030394 113356 800614 030295 094050 760618 030295 113851 770519

Earedness

Class size 517 286 197 471 315 214 498 286 216

CCFI 79 85 82 85 85 79


Heartbeat (90n 76) 030989 048115 83 0909 050986 048214 801010 040888 058213 830809

Clock (90n81) 030394 087418 92 0206 030592 068014 89 0506 030493 077914 880606




























(ORfrac14243 [215 275] po001)













143 [136ndash151])

4 Discussion


Table 7


Variable Mixed Left

Sex (male) 90 [60 133] 136 [106 174]na

Age 100 [99 101] 100 [100 101]




Left-eyed 212 [156 289]nnn 448 [377 532]nnn

Mixed-eared 140 [107 184]n 133 [110 161]nn

Left-eared 126 [90 175] 174 [145 209]nnn









41 Assessment








Table 9



1-cluster 4933925 8 9875552 860201 72 o 001 00

2-cluster 4687699 17 9391764 367749 63 o 001 846

3-cluster 4537554 26 9100139 67459 54 o 001 1304



4-cluster 4520011 35 9073717 32372 45 o 001 2174


boldface

Table 10





Handedness 010098 050589 620533 033067 087319 682012

Footedness 010099 009406 890605 010397 009802 910009

Eyedness 201268 183546 591525 042472 075538 232453

Earedness 18 1963 155233 532423 042076 075340 232354


classes

Table 8







285]nnn137 [104 181]n 127 [91 177]

Left-handed 304 [250 370]nnn 4308 [3560

5213]nnn187 [151 231]nnn 449 [378

533]nnn140 [116 169]nnn 175 [146 211]nnn


122 [110 135]nnn

365 [334 398]nnn

156 [140 174]nnn

Left-footed 181 [147 225]nnn 244 [207

289]nnn201 [166 243]nnn 349 [293

415]nnn



284]nnn



284]nnn


R2

537332 (22) po 001

363

323077 (22) po 001

224

328511 (20) po 001

224










































Table 11




Non-LNon-L 882 (852) (895) (885) 740 (729) 739 (738) 735 (726) 741 (734) 643 (6 41)

Non-LL 37 (68) (23) (34) 179 (191) 181 (182) 179 (188) 174 (180) 129 (129)

LNon-L 32 (32) (21) (31) 32 (41) 41 (42) 37 (44) 39 (46) 137 (139)

LL 49 (18) (61) (51) 49 (39) 40 (38) 48 (42) 46 (40) 91 (91)

χ 2 120966 28009 635 8038 219 4177 3109 60














































5 Limitations








6 Conclusions





classi1047297cation

Acknowledgments




201407027

References










































































































































Table 2




16 items 85215 (104) 994 993 054 [051058]

10 items 28141 (35) 998 997 054 [048059]






Footedness 473 (2) 999 998 024 [000052]

Eyedness 1949 (2) 1000 999 060 [037085]

Earedness 7331 (2) 994 982 121 [098145]



Table 3




Writing 95 94 96 95

Drawing 96


Tennis 94 94 98

Toothbrush 91 91 96

Knife 92 92 96 97

Hammer 98 98 99 99n

Match 88


Needle 69

Fly 1047298ap 93 93 97

Scissors 92 92 97

Spoon 91 91 95

Broom 68

Box 78













































37 Sidedness




Table 4




3-cluster 486644 62 1021682 178731 2394 1000 164

4-cluster 476613 83 1018012 158667 2371 1000 191

5-cluster 471353 104 1023883 148146 2350 1000 240


boldface









Table 5




Class size 849 071 079900n 021n 078n 895 028 077 890 026 084

CCFI 66 76

59n 76n 67 87 88 63LQ cutoffs 472 72 to 7 o7

441n 41 to 40n o40n 441 41 to 40 o40 441 41 to 40 o40

Writing 0 00 099 170281 720028

010099n 330660n 720028n 010099 132166 80 0119 010099 242056 740225

Thr owing 00 0099 131473 890209

010199n 223741n 920108n 010298 095536 83 0413 010198 145036 870311

Tennis 000199 121770 910504


010198n 362538n 900010n 010197 136225 83 0313 010198 124841 830413Hammer 0 00 099 091180 970103

000099n 303733n 970003n 000199 095933 91 0306 000199 095833 920206

Eraser 000298 204139 880408

Fly 1047298ap 000297 054747 851103

Scissors 0 00 099 082072 830215

Spoon 000298 172359 830511





Table 6




Footedness

Class size 632 261 106 566 347 086 595 314 091

CCFI 76 87 78 85 77 76


Ball (8460) 010298 051976 680923 010297 042769 651323 010297 052669 700822

Pebble (8466) 011089 027227 711811 030592 027027 731908 030592 046730 781309

Be etle ( 83 66) 01 0891 007228 553015 031186 017921 533116 021187 018019 572816Chair (67 51) 08 0884 105139 691516 110980 095537 711515 110782 095437 721315

Eyedness

Class size 630 141 229 567 211 220 572 201 227

CCFI 79 81 72 89 76 84


Bo ttle (95 82) 01 0693 048313 86 0806 020692 038413 86 0707 020692 048412 831007

Keyhole (9684) 010495 048016 88 0606 020692 047719 85 0708 020494 047719 870607

Gun (9070) 030394 113356 800614 030295 094050 760618 030295 113851 770519

Earedness

Class size 517 286 197 471 315 214 498 286 216

CCFI 79 85 82 85 85 79


Heartbeat (90n 76) 030989 048115 83 0909 050986 048214 801010 040888 058213 830809

Clock (90n81) 030394 087418 92 0206 030592 068014 89 0506 030493 077914 880606




























(ORfrac14243 [215 275] po001)













143 [136ndash151])

4 Discussion


Table 7


Variable Mixed Left

Sex (male) 90 [60 133] 136 [106 174]na

Age 100 [99 101] 100 [100 101]




Left-eyed 212 [156 289]nnn 448 [377 532]nnn

Mixed-eared 140 [107 184]n 133 [110 161]nn

Left-eared 126 [90 175] 174 [145 209]nnn









41 Assessment








Table 9



1-cluster 4933925 8 9875552 860201 72 o 001 00

2-cluster 4687699 17 9391764 367749 63 o 001 846

3-cluster 4537554 26 9100139 67459 54 o 001 1304



4-cluster 4520011 35 9073717 32372 45 o 001 2174


boldface

Table 10





Handedness 010098 050589 620533 033067 087319 682012

Footedness 010099 009406 890605 010397 009802 910009

Eyedness 201268 183546 591525 042472 075538 232453

Earedness 18 1963 155233 532423 042076 075340 232354


classes

Table 8







285]nnn137 [104 181]n 127 [91 177]

Left-handed 304 [250 370]nnn 4308 [3560

5213]nnn187 [151 231]nnn 449 [378

533]nnn140 [116 169]nnn 175 [146 211]nnn


122 [110 135]nnn

365 [334 398]nnn

156 [140 174]nnn

Left-footed 181 [147 225]nnn 244 [207

289]nnn201 [166 243]nnn 349 [293

415]nnn



284]nnn



284]nnn


R2

537332 (22) po 001

363

323077 (22) po 001

224

328511 (20) po 001

224










































Table 11




Non-LNon-L 882 (852) (895) (885) 740 (729) 739 (738) 735 (726) 741 (734) 643 (6 41)

Non-LL 37 (68) (23) (34) 179 (191) 181 (182) 179 (188) 174 (180) 129 (129)

LNon-L 32 (32) (21) (31) 32 (41) 41 (42) 37 (44) 39 (46) 137 (139)

LL 49 (18) (61) (51) 49 (39) 40 (38) 48 (42) 46 (40) 91 (91)

χ 2 120966 28009 635 8038 219 4177 3109 60














































5 Limitations








6 Conclusions





classi1047297cation

Acknowledgments




201407027

References
























































































































































37 Sidedness




Table 4




3-cluster 486644 62 1021682 178731 2394 1000 164

4-cluster 476613 83 1018012 158667 2371 1000 191

5-cluster 471353 104 1023883 148146 2350 1000 240


boldface









Table 5




Class size 849 071 079900n 021n 078n 895 028 077 890 026 084

CCFI 66 76

59n 76n 67 87 88 63LQ cutoffs 472 72 to 7 o7

441n 41 to 40n o40n 441 41 to 40 o40 441 41 to 40 o40

Writing 0 00 099 170281 720028

010099n 330660n 720028n 010099 132166 80 0119 010099 242056 740225

Thr owing 00 0099 131473 890209

010199n 223741n 920108n 010298 095536 83 0413 010198 145036 870311

Tennis 000199 121770 910504


010198n 362538n 900010n 010197 136225 83 0313 010198 124841 830413Hammer 0 00 099 091180 970103

000099n 303733n 970003n 000199 095933 91 0306 000199 095833 920206

Eraser 000298 204139 880408

Fly 1047298ap 000297 054747 851103

Scissors 0 00 099 082072 830215

Spoon 000298 172359 830511





Table 6




Footedness

Class size 632 261 106 566 347 086 595 314 091

CCFI 76 87 78 85 77 76


Ball (8460) 010298 051976 680923 010297 042769 651323 010297 052669 700822

Pebble (8466) 011089 027227 711811 030592 027027 731908 030592 046730 781309

Be etle ( 83 66) 01 0891 007228 553015 031186 017921 533116 021187 018019 572816Chair (67 51) 08 0884 105139 691516 110980 095537 711515 110782 095437 721315

Eyedness

Class size 630 141 229 567 211 220 572 201 227

CCFI 79 81 72 89 76 84


Bo ttle (95 82) 01 0693 048313 86 0806 020692 038413 86 0707 020692 048412 831007

Keyhole (9684) 010495 048016 88 0606 020692 047719 85 0708 020494 047719 870607

Gun (9070) 030394 113356 800614 030295 094050 760618 030295 113851 770519

Earedness

Class size 517 286 197 471 315 214 498 286 216

CCFI 79 85 82 85 85 79


Heartbeat (90n 76) 030989 048115 83 0909 050986 048214 801010 040888 058213 830809

Clock (90n81) 030394 087418 92 0206 030592 068014 89 0506 030493 077914 880606




























(ORfrac14243 [215 275] po001)













143 [136ndash151])

4 Discussion


Table 7


Variable Mixed Left

Sex (male) 90 [60 133] 136 [106 174]na

Age 100 [99 101] 100 [100 101]




Left-eyed 212 [156 289]nnn 448 [377 532]nnn

Mixed-eared 140 [107 184]n 133 [110 161]nn

Left-eared 126 [90 175] 174 [145 209]nnn









41 Assessment








Table 9



1-cluster 4933925 8 9875552 860201 72 o 001 00

2-cluster 4687699 17 9391764 367749 63 o 001 846

3-cluster 4537554 26 9100139 67459 54 o 001 1304



4-cluster 4520011 35 9073717 32372 45 o 001 2174


boldface

Table 10





Handedness 010098 050589 620533 033067 087319 682012

Footedness 010099 009406 890605 010397 009802 910009

Eyedness 201268 183546 591525 042472 075538 232453

Earedness 18 1963 155233 532423 042076 075340 232354


classes

Table 8







285]nnn137 [104 181]n 127 [91 177]

Left-handed 304 [250 370]nnn 4308 [3560

5213]nnn187 [151 231]nnn 449 [378

533]nnn140 [116 169]nnn 175 [146 211]nnn


122 [110 135]nnn

365 [334 398]nnn

156 [140 174]nnn

Left-footed 181 [147 225]nnn 244 [207

289]nnn201 [166 243]nnn 349 [293

415]nnn



284]nnn



284]nnn


R2

537332 (22) po 001

363

323077 (22) po 001

224

328511 (20) po 001

224










































Table 11




Non-LNon-L 882 (852) (895) (885) 740 (729) 739 (738) 735 (726) 741 (734) 643 (6 41)

Non-LL 37 (68) (23) (34) 179 (191) 181 (182) 179 (188) 174 (180) 129 (129)

LNon-L 32 (32) (21) (31) 32 (41) 41 (42) 37 (44) 39 (46) 137 (139)

LL 49 (18) (61) (51) 49 (39) 40 (38) 48 (42) 46 (40) 91 (91)

χ 2 120966 28009 635 8038 219 4177 3109 60














































5 Limitations








6 Conclusions





classi1047297cation

Acknowledgments




201407027

References






















































































































Table 5




Class size 849 071 079900n 021n 078n 895 028 077 890 026 084

CCFI 66 76

59n 76n 67 87 88 63LQ cutoffs 472 72 to 7 o7

441n 41 to 40n o40n 441 41 to 40 o40 441 41 to 40 o40

Writing 0 00 099 170281 720028

010099n 330660n 720028n 010099 132166 80 0119 010099 242056 740225

Thr owing 00 0099 131473 890209

010199n 223741n 920108n 010298 095536 83 0413 010198 145036 870311

Tennis 000199 121770 910504


010198n 362538n 900010n 010197 136225 83 0313 010198 124841 830413Hammer 0 00 099 091180 970103

000099n 303733n 970003n 000199 095933 91 0306 000199 095833 920206

Eraser 000298 204139 880408

Fly 1047298ap 000297 054747 851103

Scissors 0 00 099 082072 830215

Spoon 000298 172359 830511





Table 6




Footedness

Class size 632 261 106 566 347 086 595 314 091

CCFI 76 87 78 85 77 76


Ball (8460) 010298 051976 680923 010297 042769 651323 010297 052669 700822

Pebble (8466) 011089 027227 711811 030592 027027 731908 030592 046730 781309

Be etle ( 83 66) 01 0891 007228 553015 031186 017921 533116 021187 018019 572816Chair (67 51) 08 0884 105139 691516 110980 095537 711515 110782 095437 721315

Eyedness

Class size 630 141 229 567 211 220 572 201 227

CCFI 79 81 72 89 76 84


Bo ttle (95 82) 01 0693 048313 86 0806 020692 038413 86 0707 020692 048412 831007

Keyhole (9684) 010495 048016 88 0606 020692 047719 85 0708 020494 047719 870607

Gun (9070) 030394 113356 800614 030295 094050 760618 030295 113851 770519

Earedness

Class size 517 286 197 471 315 214 498 286 216

CCFI 79 85 82 85 85 79


Heartbeat (90n 76) 030989 048115 83 0909 050986 048214 801010 040888 058213 830809

Clock (90n81) 030394 087418 92 0206 030592 068014 89 0506 030493 077914 880606




























(ORfrac14243 [215 275] po001)













143 [136ndash151])

4 Discussion


Table 7


Variable Mixed Left

Sex (male) 90 [60 133] 136 [106 174]na

Age 100 [99 101] 100 [100 101]




Left-eyed 212 [156 289]nnn 448 [377 532]nnn

Mixed-eared 140 [107 184]n 133 [110 161]nn

Left-eared 126 [90 175] 174 [145 209]nnn









41 Assessment








Table 9



1-cluster 4933925 8 9875552 860201 72 o 001 00

2-cluster 4687699 17 9391764 367749 63 o 001 846

3-cluster 4537554 26 9100139 67459 54 o 001 1304



4-cluster 4520011 35 9073717 32372 45 o 001 2174


boldface

Table 10





Handedness 010098 050589 620533 033067 087319 682012

Footedness 010099 009406 890605 010397 009802 910009

Eyedness 201268 183546 591525 042472 075538 232453

Earedness 18 1963 155233 532423 042076 075340 232354


classes

Table 8







285]nnn137 [104 181]n 127 [91 177]

Left-handed 304 [250 370]nnn 4308 [3560

5213]nnn187 [151 231]nnn 449 [378

533]nnn140 [116 169]nnn 175 [146 211]nnn


122 [110 135]nnn

365 [334 398]nnn

156 [140 174]nnn

Left-footed 181 [147 225]nnn 244 [207

289]nnn201 [166 243]nnn 349 [293

415]nnn



284]nnn



284]nnn


R2

537332 (22) po 001

363

323077 (22) po 001

224

328511 (20) po 001

224










































Table 11




Non-LNon-L 882 (852) (895) (885) 740 (729) 739 (738) 735 (726) 741 (734) 643 (6 41)

Non-LL 37 (68) (23) (34) 179 (191) 181 (182) 179 (188) 174 (180) 129 (129)

LNon-L 32 (32) (21) (31) 32 (41) 41 (42) 37 (44) 39 (46) 137 (139)

LL 49 (18) (61) (51) 49 (39) 40 (38) 48 (42) 46 (40) 91 (91)

χ 2 120966 28009 635 8038 219 4177 3109 60














































5 Limitations








6 Conclusions





classi1047297cation

Acknowledgments




201407027

References




































































































































(ORfrac14243 [215 275] po001)













143 [136ndash151])

4 Discussion


Table 7


Variable Mixed Left

Sex (male) 90 [60 133] 136 [106 174]na

Age 100 [99 101] 100 [100 101]




Left-eyed 212 [156 289]nnn 448 [377 532]nnn

Mixed-eared 140 [107 184]n 133 [110 161]nn

Left-eared 126 [90 175] 174 [145 209]nnn









41 Assessment








Table 9



1-cluster 4933925 8 9875552 860201 72 o 001 00

2-cluster 4687699 17 9391764 367749 63 o 001 846

3-cluster 4537554 26 9100139 67459 54 o 001 1304



4-cluster 4520011 35 9073717 32372 45 o 001 2174


boldface

Table 10





Handedness 010098 050589 620533 033067 087319 682012

Footedness 010099 009406 890605 010397 009802 910009

Eyedness 201268 183546 591525 042472 075538 232453

Earedness 18 1963 155233 532423 042076 075340 232354


classes

Table 8







285]nnn137 [104 181]n 127 [91 177]

Left-handed 304 [250 370]nnn 4308 [3560

5213]nnn187 [151 231]nnn 449 [378

533]nnn140 [116 169]nnn 175 [146 211]nnn


122 [110 135]nnn

365 [334 398]nnn

156 [140 174]nnn

Left-footed 181 [147 225]nnn 244 [207

289]nnn201 [166 243]nnn 349 [293

415]nnn



284]nnn



284]nnn


R2

537332 (22) po 001

363

323077 (22) po 001

224

328511 (20) po 001

224










































Table 11




Non-LNon-L 882 (852) (895) (885) 740 (729) 739 (738) 735 (726) 741 (734) 643 (6 41)

Non-LL 37 (68) (23) (34) 179 (191) 181 (182) 179 (188) 174 (180) 129 (129)

LNon-L 32 (32) (21) (31) 32 (41) 41 (42) 37 (44) 39 (46) 137 (139)

LL 49 (18) (61) (51) 49 (39) 40 (38) 48 (42) 46 (40) 91 (91)

χ 2 120966 28009 635 8038 219 4177 3109 60














































5 Limitations








6 Conclusions





classi1047297cation

Acknowledgments




201407027

References

















































































































41 Assessment








Table 9



1-cluster 4933925 8 9875552 860201 72 o 001 00

2-cluster 4687699 17 9391764 367749 63 o 001 846

3-cluster 4537554 26 9100139 67459 54 o 001 1304



4-cluster 4520011 35 9073717 32372 45 o 001 2174


boldface

Table 10





Handedness 010098 050589 620533 033067 087319 682012

Footedness 010099 009406 890605 010397 009802 910009

Eyedness 201268 183546 591525 042472 075538 232453

Earedness 18 1963 155233 532423 042076 075340 232354


classes

Table 8







285]nnn137 [104 181]n 127 [91 177]

Left-handed 304 [250 370]nnn 4308 [3560

5213]nnn187 [151 231]nnn 449 [378

533]nnn140 [116 169]nnn 175 [146 211]nnn


122 [110 135]nnn

365 [334 398]nnn

156 [140 174]nnn

Left-footed 181 [147 225]nnn 244 [207

289]nnn201 [166 243]nnn 349 [293

415]nnn



284]nnn



284]nnn


R2

537332 (22) po 001

363

323077 (22) po 001

224

328511 (20) po 001

224










































Table 11




Non-LNon-L 882 (852) (895) (885) 740 (729) 739 (738) 735 (726) 741 (734) 643 (6 41)

Non-LL 37 (68) (23) (34) 179 (191) 181 (182) 179 (188) 174 (180) 129 (129)

LNon-L 32 (32) (21) (31) 32 (41) 41 (42) 37 (44) 39 (46) 137 (139)

LL 49 (18) (61) (51) 49 (39) 40 (38) 48 (42) 46 (40) 91 (91)

χ 2 120966 28009 635 8038 219 4177 3109 60














































5 Limitations








6 Conclusions





classi1047297cation

Acknowledgments




201407027

References




















































































































































Table 11




Non-LNon-L 882 (852) (895) (885) 740 (729) 739 (738) 735 (726) 741 (734) 643 (6 41)

Non-LL 37 (68) (23) (34) 179 (191) 181 (182) 179 (188) 174 (180) 129 (129)

LNon-L 32 (32) (21) (31) 32 (41) 41 (42) 37 (44) 39 (46) 137 (139)

LL 49 (18) (61) (51) 49 (39) 40 (38) 48 (42) 46 (40) 91 (91)

χ 2 120966 28009 635 8038 219 4177 3109 60














































5 Limitations








6 Conclusions





classi1047297cation

Acknowledgments




201407027

References
























































































































































5 Limitations








6 Conclusions





classi1047297cation

Acknowledgments




201407027

References


















































































































6 Conclusions





classi1047297cation

Acknowledgments




201407027

References








































































































































































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